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Abstract
Objective: To estimate the infection rate of close contacts of COVID-19 cases, and to evaluate the risk of COVID-19 under different exposure conditions. Methods: A prospective study was used to conduct continuous quarantine medical observations of close contacts of people infected with COVID-19, collect epidemiological, clinical manifestations, and laboratory test data to estimate the infection rate of close contacts under different exposures. Results: The epidemiological curve of COVID-19 in Ningbo showed persistent human-to-human characteristics. A total of 2 147 close contacts were tracked and investigated. The total infection rate was 6.15%. The infection rates of confirmed cases and positive contacts were 6.30% and 4.11%, respectively. The difference was not statistically significant (P>0.05). Among close contacts of different relationships, friends/pilgrims (22.31%), family members (18.01%), and relatives (4.73%) have a higher infection rate, and close contacts of medical staff were not infected. Differences in infection rates among the close contacts were statistically significant (P<0.005). Living with the case (13.26%), taking the same transportation (11.91%), and dining together (7.18%) are high risk factors for infection. Cross-infection in the hospital should not be ignored (1.94%). The median of incubation period is 5 days. Conclusion: The infection rate of close contacts of COVID-19 cases is high, and isolation medical observation measures should be implemented in strict accordance with the close contact management plan.
... It has been known that procalcitonin is effective as an inflammatory marker in detecting bacterial infection and for suspecting superadded infection in virally infected patients. It is believed that bacteria and viruses regulate procalcitonin production through interferon signaling [17] . ...
... There is mounting evidence that many COVID-19 individuals are asymptomatic or only have minor symptoms, yet they can still spread the virus to other people. It is challenging to screen for asymptomatic infections, which makes it more challenging to prevent and control this epidemic nationally [17] . ...
... When SARS-CoV-2 nucleic acid is positively identified in patient samples by RT-PCR, an infection is considered asymptomatic if there are no conventional clinical symptoms or signs, and there are no obvious abnormalities in imaging, including lung computed tomography. Numerous studies have demonstrated that they are a significant source of illness dissemination and have the same infectivity as symptomatic individuals [17] . Many studies focused on correlation between procalcitonin and severity of COVID infection and its efficacy as a prognostic value, but no studies tested the efficacy of procalcitonin as a predictive marker for asymptomatic COVID infection. ...
... Of these, 44 reported cluster/outbreak investigations (presented in chronological order in Additional file 1: Table SG.1) [4-7, 9, 10, 14, 15, 17, 18, 20-28, 30-34, 36-44, 46-51, 53-55, 57, 58], six reported comparative epidemiological studies that allowed calculation of relative risks of transmission based on the index case's symptom status during exposure of their close contacts (for example, transmission associated with presymptomatic exposure versus transmission associated with symptomatic exposure) [11,12,19,35,52,56], and five reported mathematical modelling of epidemic spread [8,13,16,29,45]. More than half of the included studies referred to investigations of SARS-CoV-2 transmission in mainland China, reflecting the emergence and initial investigation of COVID-19 there; the remainder reported evidence from Germany, Hong Kong, Italy, Japan, Malaysia, Singapore, South Korea, Switzerland, Taiwan, USA and Vietnam, reflecting the pandemic spread as time progressed (see Additional file 1: Table SF.1 for further details). ...
... In several instances, the same cluster/outbreak was reported independently in more than one article (for example, three separate articles reported or commented on a single cluster/outbreak in Germany) [7,26,41] or the same data were analysed differently across multiple articles (for example, three articles reported different analyses of relative risks of transmission based on the index case's symptom status during an outbreak in China) [11,19,52]. Similarly, there were several instances in which a single article reported multiple clusters/outbreaks (for example, one article summarised evidence from several clusters in Singapore that were likely to be associated with presymptomatic transmission) [46]. ...
... Relative risks of transmission associated with presymptomatic exposure versus transmission associated with symptomatic exposure (two studies) [12,35], and transmission associated with asymptomatic exposure compared to either presymptomatic or symptomatic exposure (four studies reported across six articles) [11,12,19,35,52,56] are presented in the evidence tables for the comparative epidemiological studies (see Additional file 1: ...
... Este indicador resulta estático en el tiempo. (8,9,10,11) Para el SARS-CoV-2, en los inicios de la epidemia el R0 se calculó entre 2,24 (IC 95 %:1,96-2,55) y 3,58 (IC 95 %: 2,89-4,39), es decir, que una persona infectada puede generar aproximadamente de 2 a 4 personas (aunque se describen "supercontagiadores" capaces de infectar un mayor número de individuos), lo que significa que la infección puede propagarse rápida y ampliamente entre la población. (8,9,10) A diferencia del R0, el número reproductivo efectivo (Re) varía temporalmente con la tasa de contacto efectiva, el comportamiento y la organización social, y la fracción de recuperados y fallecidos durante el curso epidémico. ...
... (8,9,10,11) Para el SARS-CoV-2, en los inicios de la epidemia el R0 se calculó entre 2,24 (IC 95 %:1,96-2,55) y 3,58 (IC 95 %: 2,89-4,39), es decir, que una persona infectada puede generar aproximadamente de 2 a 4 personas (aunque se describen "supercontagiadores" capaces de infectar un mayor número de individuos), lo que significa que la infección puede propagarse rápida y ampliamente entre la población. (8,9,10) A diferencia del R0, el número reproductivo efectivo (Re) varía temporalmente con la tasa de contacto efectiva, el comportamiento y la organización social, y la fracción de recuperados y fallecidos durante el curso epidémico. Si las medidas de control son efectivas el Re debe estar por debajo de 1. (11) En los glosarios epidemiológicos suele llamarse "brote" al episodio en el cual dos o más casos tienen alguna relación entre sí, atendiendo al momento de inicio, lugar y las características de las personas implicadas. ...
Introducción:
Una oportuna investigación de los eventos epidemiológicos de la COVID-19 garantiza minimizar la propagación de la enfermedad en la población.
Objetivos:
Caracterizar el brote de transmisión comunitaria de COVID-19 en un municipio de La Habana.
Métodos:
Estudio transversal de casos positivos de infección por SARS-CoV-2 del brote Catedral en La Habana Vieja, en 2021. Las variables analizadas fueron: edad, sexo, manzana de residencia, fecha de inicio de síntomas, fecha de diagnóstico, forma clínica, tipo de caso. Se utilizó la metodología para el estudio de brotes. Se calcularon porcentajes, diferencias de proporciones, tasas, número reproductivo efectivo y parámetro de dispersión con intervalos de confianza de 95 %.
Resultados:
Se notificó el brote el 23 de marzo y se cerró el 22 de abril con 106 casos (tasa de ataque 4,51 %), el pico en la notificación se produjo el 29 de marzo con 40 casos (37,73 %). La edad media fue de 43 años. Resultaron más afectados los adultos de 60 y más años (30,18 %), las mujeres (58,49 %) y la manzana 0024 (45,28 % de los casos). El 77,3 % no presentó síntomas, entre ellos dos superdispersores; los sintomáticos fueron leves y no hubo fallecidos. El número reproductivo efectivo global fue de 0,94 (IC: 0,70-1,21); superior en los asintomáticos (11,43 versus 4,00); y el parámetro de dispersión de 0,89 (IC: 0,51-2,09), superior en los sintomáticos (1,06 versus 0,69).
Conclusiones:
El control epidemiológico oportuno ante cada caso permitió la corta duración del brote y que no hubiesen fallecidos.
... Psychological distress or anxiety of the infection risk in the healthcare might be an influential factor (Bavel et al., 2020). And the COVID-19 policies such as keeping social distance, shutdown of transportation, quarantine requirements for infected people and close contacts might also stop people from accessing healthcare places (Bavel et al., 2020;Chen et al., 2020;Nikiforiadis et al., 2022). In addition, before the outbreak of COVID-19, many influential factors have been studied. ...
... Many behavioural change interventions are potential to affect the stable operation of whole healthcare system. Examples are factors (i.e., interventions) such as personal health condition, transportation, healthcare medical capability that have been existing before the pandemic (Comber et al., 2011;Lee et al., 2014), and mask mandatory, social distance and vaccination requirements have occurred after the COVID-19 outbreak (Bavel et al., 2020;Chen et al., 2020;Nikiforiadis et al., 2022). In the psychological science research field, COM-B model has been well-established by (Michie et al., 2011) overcoming the limitations of the other 19 behaviour change frameworks (Perros et al., 2022). ...
The global pandemic of COVID-19 has been influencing people’s lives and the cities. Not only people’s physical and mental health have been threatened, but also the city operation has been profoundly affected from different perspectives (e.g., social and economic) permanently. How cities can efficiently react and response to improve city resilience is an urgent issue to be addressed. The healthcare system as a vital part of the city systems is confronting intense pressure and many challenges under this emergent public health crisis of COVID-19, which might cause huge impacts on the whole city’s operation. Also, human beings as the direct victims of this public health crisis, their behaviour changes impacts on the healthcare system and the city could have been inevitable but have been neglected. In this context, this paper intends to study the citizen healthcare accessing behaviours changes in the post-pandemic era, and to unearth their impacts on the healthcare system and the city operation. For this purpose, first, a framework of influential factors for healthcare accessing was established based on a bidirectional “capability, opportunity, motivation, and behaviour” (COM-B) model and the comprehensive literature review. In which, 43 factors that would influence citizen healthcare accessing behaviour were identified and classified. Thus, based on the proposed framework, two cases (i.e., UK and China) were analysed in depth and compared based on a questionnaire survey to evaluate the factor importance and relationships under different scenarios. And the most influential factors based on analysis results are classified into 12 aspects (e.g., healthcare capability, policy support, information updating etc.). Further, a novel behaviour-healthcare system-city model based on the COM-B model was developed to rethink and indicate the relationships among citizen behaviour, healthcare system and city operation. The research results can be used by policymakers and researchers to improve the city resilience by enabling immediate responses to city systems and citizens behaviours confronting city emergencies.
... He et al. [15] found that asymptomatic patients had lower infection rates than symptomatic patients, and that patients infected by asymptomatic patients were more likely to be asymptomatic patients. Chen Yi et al. [16] found that the viral infection rates were about 6.30% and 4.11% for contact with symptomatic and asymptomatic patients, respectively. Zhou et al. [17] found that some asymptomatic patients transformed into symptomatic patients, and some patients remained asymptomatic patients. ...
... According to He et al. [15] and Chen Yi et al. [16], the infection rates and the interval length differ in different types of patients. Therefore, four different types of infection rates are assumed in Assumption (2), and the two different types of disappearing rates are assumed in Assumption (3). ...
After over three years of COVID-19, it has become clear that infectious diseases are difficult to eradicate, and humans remain vulnerable under their influence in a long period. The presence of presymptomatic and asymptomatic patients is a significant obstacle to preventing and eliminating infectious diseases. However, the long-term transmission of infectious diseases involving asymptomatic patients still remains unclear. To address this issue, this paper develops a novel Markov process for infectious diseases with asymptomatic patients by means of a continuous-time level-dependent quasi-birth-and-death (QBD) process. The model accurately captures the transmission of infectious diseases by specifying several key parameters (or factors). To analyze the role of asymptomatic and symptomatic patients in the infectious disease transmission process, a simple sufficient condition for the stability of the Markov process of infectious diseases is derived using the mean drift technique. Then, the stationary probability vector of the QBD process is obtained by using RG-factorizations. A method of using the stationary probability vector is provided to obtain important performance measures of the model. Finally, some numerical experiments are presented to demonstrate the model's feasibility through analyzing COVID-19 as an example. The impact of key parameters on the system performance evaluation and the infectious disease transmission process are analyzed. The methodology and results of this paper can provide theoretical and technical support for the scientific control of the long-term transmission of infectious diseases, and we believe that they can serve as a foundation for developing more general models of infectious disease transmission.
... Nine studies contained detailed data on the secondary infection number of close contacts of symptomatic infections and asymptomatic infections. [19][20][21][22][23][24][25][26][27] The close contact data sets of all 9 studies were from China, indicating that China had more detailed and comprehensive classifications of COVID-19 close contacts than other countries and focused more on symptoms and the severity of cases. ...
... Twenty-two studies, from China, Iran, Singapore, America, and Spain, contained detailed data on the number of households and total close contacts. 19,[22][23][24][25][26][28][29][30][32][33][34][35][36][37][38][39][42][43][44][45][46] The meta-analysis for binary outcomes used total close contacts as the control group. We used "live together" as the criterion for identifying close household contacts, and studies declaring close contacts as "family members" were excluded. ...
Objective
Contact tracing plays an essential role in mitigating the impact of an epidemic. During the COVID‐19 pandemic, studies of those who have been in close contact with confirmed cases offer critical insights to understand the epidemiological characteristics of SARS‐CoV‐2 better. This study conducts a meta‐analysis of existing studies' infection rates and affecting factors.
Methods
We searched PubMed, Web of Science and CNKI from the inception to April 30 2022 to identify systematic reviews. Two reviewers independently extracted the data and assessed risk of bias. Meta‐analyses were conducted to calculate pooled estimates by using Stata/SE 15.1 software.
Results
There were 47 studies in the meta‐analysis. Among COVID‐19 close contacts, older age (RR = 1.94, 95% CI: 1.70, 2.21), contacts in households (RR = 2.83, 95% CI: 2.20, 3.65), and people in close contact with symptomatic infections (RR = 3.62, 95% CI: 1.88, 6.96) were associated with higher infection rates.
Conclusion
On average, each primary infection corresponded to 5.8 close contacts. Among COVID‐19 close contacts, older age and contacts in households were associated with higher infection rates, and people in close contact with symptomatic infections had three times higher risk of infection compared to people in close contact with asymptomatic infections. In general, there are significantly more studies from China about close contacts, and the infection rate among close contacts was lower compared to other countries.
... Additionally, one study showed that the clinical manifestations of infected contacts varied according to the type of contact with index cases, that is, secondary cases were more likely to develop symptoms when they were exposed to symptomatic index cases and be asymptomatic when they were exposed to asymptomatic index cases [105]. Chen et al. proposed that asymptomatic infected persons were more likely to transmit asymptomatic infections [108]. ...
... Some other researchers also used a mathematical model to estimate the transmissibility of asymptomatic COVID-19, which may provide additional information. In a prospective study that collected data of close contacts of COVID-19 patients, Chen et al. found no substantial difference between the infection rates of the close contacts of confirmed cases and asymptomatic infections, which were 6.30% (126/2,001) and 4.11% (6/146), respectively [108]. However, He et al. interpreted the outcomes with the susceptibleexposed-infectious-removed (SEIR) model and came to a different conclusion that the relative transmissibility of asymptomatic individuals could be significantly less than that of the symptomatic individuals. ...
With the presence of Coronavirus Disease 2019 (COVID-19) asymptomatic infections detected, their proportion, transmission potential, and other aspects such as immunity and related emerging challenges have attracted people’s attention. We have found that based on high-quality research, asymptomatic infections account for at least one-third of the total cases, whereas based on systematic review and meta-analysis, the proportion is about one-fifth. Evaluating the true transmission potential of asymptomatic cases is difficult but critical, since it may affect national policies in response to COVID-19. We have summarized the current evidence and found, compared with symptomatic cases, the transmission capacity of asymptomatic individuals is weaker, even though they have similar viral load and relatively short virus shedding duration. As the outbreak progresses, asymptomatic infections have also been found to develop long COVID-19. In addition, the role of asymptomatic infection in COVID-19 remains to be further revealed as the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants continue to emerge. Nevertheless, as asymptomatic infections transmit the SARS-CoV-2 virus silently, they still pose a substantial threat to public health. Therefore, it is essential to conduct screening to obtain more knowledge about the asymptomatic infections and to detect them as soon as possible; meanwhile, management of them is also a key point in the fight against COVID-19 community transmission. The different management of asymptomatic infections in various countries are compared and the experience in China is displayed in detail.
... Unfortunately, 19 patients, 13 males and 6 females, died from complications related to SARS-CoV-2 infection, while the number of deaths among patients with end-stage renal disease who were on regular hemodialysis with negative tests for SARS-CoV-2 infection during the study period was ten deaths from a total of 305 patients (Mortality percentage 3.9%). [15][16][17][18][19][20][21]. ...
... [5][6][7] The implementation of widespread testing and strict quarantine procedures for close contacts, including rigorous symptom monitoring and frequent testing, allowed for detection of SARS-CoV-2 transmission from asymptomatic individuals in ways that had not been logistically feasible for influenza virus. [8][9][10][11] Realising the importance of asymptomatic SARS-CoV-2 infection has reignited discussions about the contribution of asymptomatic infections to influenza virus transmission and how it might affect the effectiveness of influenza control measures. ...
... Te contact between healthy and those hospitalized is shown by ξ 4 , as in many countries of the world with fewer medical facilities [54]. Te healthy individuals and their contact with the exposed individuals are possible because the virus can easily transfer to healthy individuals through coughing, shaking hands, fu, etc., and this fact has been documented in the literature, see [55][56][57][58]. It is well known that individuals in the asymptomatic class have strong immunity and they do not show the disease symptoms until it is tested to be identifed or hard to screen for and can easily transmit the infection to healthy people. ...
To evaluate the probable effects of the COVID-19 outbreak on Saudi Arabia, a novel dynamical model is developed. Using the most recent instances of COVID-19 infection that have been reported in Saudi Arabia, we examine the roles of quarantine and hospitalization. The model’s mathematical outcomes are displayed. The model’s infection-free equilibrium is displayed, and asymptotically, it is determined to be both locally and globally stable. We demonstrate that the model is locally asymptotically stable (LAS) for the basic reproduction R 0 < 1 . The model is globally asymptotically stable (GAS) when R 0 ≤ 1 . To estimate the model parameters, recent COVID-19 instances in KSA that began between May 1, 2022, and August 4, 2022, are taken into account. We achieve the needed data fitting considering the approach of nonlinear least square, and we demonstrate that the predicted basic reproduction number is R 0 ≈ 1.2988 . Graphical representations of the calculated parameters and their effects on disease eradication are provided. The findings show that the most effective way to reduce the number of new instances of infection is to limit the contact of exposed, asymptomatic, symptomatic, and hospitalized people with vulnerable. The percentage of exposed people who are quarantined also plays a big part in lowering the number of infected cases.
... It has been reported that the period of positive nucleic acid tests (the interval from the first day of positive nucleic acid tests to the first day of continuous negative tests) could be up to 3 weeks (ranging from 1 to 24 days) in ASP [11,12]. In addition, asymptomatic infections seem to have the same infectivity as symptomatic infections [8,[13][14][15] and laboratory and epidemiological evidence suggests that individuals who never develop symptoms do represent a source of potentially transmissible SARS-CoV-2 [16][17][18]. ...
... This feature determines the high concealment of the spread of COVID-19, and leads to an increase in the difficulty of epidemic prevention and control. There have been a large number of research results on asymptomatic infections of new coronary pneumonia, including age distribution, average proportion, and transmission intensity [5][6][7]. In addition, some researchers have studied the spread of COVID-19 by establishing dynamic models including asymptomatic infections. ...
The COVID-19 epidemic has been spreading around the world for nearly three years, and asymptomatic infections have exacerbated the spread of the epidemic. To analyse and evaluate the role of asymptomatic infections in the spread of the epidemic, we establish an improved COVID-19 infectious disease dynamics model. We fit the epidemic data in the four time periods corresponding to the selected 614G, Alpha, Delta and Omicron variants and obtain the proportion of asymptomatic persons among the infected persons gradually increased and with the increase of the detection ratio, the cumulative number of cases has dropped significantly, but the decline in the proportion of asymptomatic infections is not obvious. Therefore, in view of the hidden transmission of asymptomatic infections, the cooperation between various epidemic prevention and control policies is required to effectively curb the spread of the epidemic.
... Contrary to this, here we report an asymptomatic carrier of Covid-19 with prolonged viral shedding detected by RT PCR. Studies have shown that asymptomatic infections have the same infectivity as symptomatic infections [4] . And with a prolonged duration of viral shedding, the risk of transmission is more. ...
... Most asymptomatic infected people do not seek medical assistance due to the lack of obvious clinical signs and poor prevention awareness, and this increases the rapid spread of COVID-19. 2 Because of the differences in sociocultural, political, and economic contexts between countries, there has been no consensus about the best public health strategy for pandemic, to reduce their fatigue and help them cope with perceived uncomfortable symptoms. This study provides a basis for further intervention and crisis management for hospital nursing administrators during the COVID-19 pandemic. ...
Objective:
Given the immense stress faced by medical staff during the COVID-19 pandemic, this study aimed to evaluate the relationship between mindful attention awareness, fatigue, and perceived symptoms among frontline nurses who performed nucleic acid sample collection during the COVID-19 pandemic, to reduce their fatigue and help them cope with perceived uncomfortable symptoms.
Methods:
A convenience sampling method was used to survey nurses who travelled to Hainan for nucleic acid sampling in August 2022 using an online (WeChat) questionnaire. A total of 514 frontline nurses who performed nucleic acid tests completed the questionnaire. The questionnaire covered basic demographic information, Mindful Attention Awareness Scale (MAAS) ratings, and Fatigue Severity Scale (FSS) ratings. Spearman correlation analysis was used to separate the relationship between MASS and FSS, and univariate and multivariate factor analyses were used to explore the relevant influences contributing to the occurrence of fatigue.
Results:
A total of 514 individuals completed the survey,93.97% (n=483) were female, mean age was 31.15 ± 5.7, MASS score was 69.01 ± 13.53, and 296 (57.59%) nurses experienced symptoms of fatigue during the auxiliary period. Spearman correlation analysis showed that FSS was associated with MASS. Multifactorial analysis showed that sex, age, marital status, fertility status, years of work, adaptation to dietary habits, hidrorrhea, and MAAS scores affected the presence of fatigue symptoms among the medical staff in Hainan (P<0.05).
Conclusion:
The psychological status of frontline nurses undergoing nucleic acid testing during the pandemic was poor, and the appearance of fatigue symptoms could be effectively reduced by increasing levels of positive thinking among medical staff to help them cope with public health emergencies.
... A study in China suggested that symptomatic cases were more likely to spread COVID-19 than asymptomatic cases. 12 A meta-analysis suggested that face mask wearing could significantly reduce the risk of SARS-CoV-2 infection (odds ratio 0.44, 95% CI 0.21-0.93, I 2 52.0%). ...
On 1 Dec 2020, the Thai Department of Disease Control was notified of five COVID-19 infections among passengers on a flight from Switzerland to Thailand. The objectives of this investigation were to confirm the outbreak, describe epidemiological characteristics, and identify the source of infection. We performed a descriptive study and contact tracing among the flight’s passengers. We interviewed the cases and reviewed their medical records, as well as an environmental survey of the state quarantine facility. Whole genome sequencing to determine the percentage alignment identity for RT-PCR-positive cases was conducted. Thirteen infected passengers out of 107 people on the flight (12.1%) were identified. The suspected index case was a symptomatic passenger, non-mask-wearing passenger. Five of the 13 confirmed cases shared a similar genomic pattern (98–100% alignment identity), and four cases sat within one row either in front of or behind the suspected index case. The genomes of the cases were more similar to each other than those uploaded to the GISAID database from Switzerland. The symptomatic COVID-19 passenger without mask wearing was suspected to be the source. Mask wearing should be mandated on flight to prevent spreading of respiratory infectious diseases.
... For the proportion of asymptomatic cases, we chose a conservative approach in which the percentage of asymptomatic infections was 50% [2]. For the parameters related to transmissibility of the different subpopulations, we assumed a variety of values that have been used in some studies [4,81,[107][108][109][110]. In particular, we assumed that the transmissibility of the 55+ age group is half that of the 15-54 age group. ...
Vaccination against the coronavirus disease 2019 (COVID-19) started in early December of 2020 in the USA. The efficacy of the vaccines vary depending on the SARS-CoV-2 variant. Some countries have been able to deploy strong vaccination programs, and large proportions of their populations have been fully vaccinated. In other countries, low proportions of their populations have been vaccinated, due to different factors. For instance, countries such as Afghanistan, Cameroon, Ghana, Haiti and Syria have less than 10% of their populations fully vaccinated at this time. Implementing an optimal vaccination program is a very complex process due to a variety of variables that affect the programs. Besides, science, policy and ethics are all involved in the determination of the main objectives of the vaccination program. We present two nonlinear mathematical models that allow us to gain insight into the optimal vaccination strategy under different situations, taking into account the case fatality rate and age-structure of the population. We study scenarios with different availabilities and efficacies of the vaccines. The results of this study show that for most scenarios, the optimal allocation of vaccines is to first give the doses to people in the 55+ age group. However, in some situations the optimal strategy is to first allocate vaccines to the 15–54 age group. This situation occurs whenever the SARS-CoV-2 transmission rate is relatively high and the people in the 55+ age group have a transmission rate 50% or less that of those in the 15–54 age group. This study and similar ones can provide scientific recommendations for countries where the proportion of vaccinated individuals is relatively small or for future pandemics.
... For instance, in [46], the authors concluded that asymptomatic carriers have a higher viral load and, taking into account that asymptomatic carriers may have more physical contacts, it is possible to assume that β A > β I . However, there are a variety of results for each region or country, as can be seen in [47][48][49][50][51]. ...
The aim of this paper is to investigate the qualitative behavior of the COVID-19 pandemic under an initial vaccination program. We constructed a mathematical model based on a nonlinear system of delayed differential equations. The time delay represents the time that the vaccine takes to provide immune protection against SARS-CoV-2. We investigate the impact of transmission rates, vaccination, and time delay on the dynamics of the constructed system. The model was developed for the beginning of the implementation of vaccination programs to control the COVID-19 pandemic. We perform a stability analysis at the equilibrium points and show, using methods of stability analysis for delayed systems, that the system undergoes a Hopf bifurcation. The theoretical results reveal that under some conditions related to the values of the parameters and the basic reproduction number, the system approaches the disease-free equilibrium point, but if the basic reproduction number is larger than one, the system approaches endemic equilibrium and SARS-CoV-2 cannot be eradicated. Numerical examples corroborate the theoretical results and the methodology. Finally, conclusions and discussions about the results are presented.
... On the basis of our selection criteria, we excluded 88 of those studies, and 23 met our inclusion criteria (Table S1) . Combining with 140 studies identified from previous reviews [41][42][43][44][45][46][47][48][49][50][51], there were 163 studies included in our analysis ( Figure S1; Table S2). Overall, 163 studies provided 179 estimates of household SAR with 326,031 cases among 2,009,859 household contacts ( Figure 1). ...
Background
Accurate estimation of household secondary attack rate (SAR) is crucial to understand the transmissibility of SARS-CoV-2. The impact of population-level factors, such as transmission intensity in the community on SAR estimates are however rarely explored.
Methods
In this study, we included articles with original data to compute the household SAR. To determine the impact of transmission intensity in the community on household SAR estimates, we explored the association between SAR estimates and the incidence rate of cases by country during the study period.
Results
We identified 163 studies to extract data on SARs from 326,031 cases and 2,009,859 household contacts. The correlation between incidence rate of cases during the study period and SAR estimates was 0.37 (95% CI: 0.24-0.49). We found that doubling incidence rate of cases during the study period was associated with a 1.2% (95% CI: 0.5%, 1.8%) higher household SAR.
Conclusions
Our findings suggest that the incidence rate of cases during the study period is associated with higher SAR. Ignoring this factor may overestimate SARs, especially for regions with high incidences, which further impacts control policies and epidemiological characterization of emerging variants.
... It is obvious that asymptomatic people that do not have obvious disease symptoms play a significant role in disease transmission, and it is very difficult to control the disease until we can increase the number of testing for COVID-19 people. The spread due to exposed individuals has been documented in several clinical studies [27][28][29][30]. The above discussion can be shown mathematically in the form of a nonlinear model governed by the evolutionary differential equations given by: ...
Natural symmetry exists in several phenomena in physics, chemistry, and biology. Incorporating these symmetries in the differential equations used to characterize these processes is thus a valid modeling assumption. The present study investigates COVID-19 infection through the stochastic model. We consider the real infection data of COVID-19 in Saudi Arabia and present its detailed mathematical results. We first present the existence and uniqueness of the deterministic model and later study the dynamical properties of the deterministic model and determine the global asymptotic stability of the system for R0≤1. We then study the dynamic properties of the stochastic model and present its global unique solution for the model. We further study the extinction of the stochastic model. Further, we use the nonlinear least-square fitting technique to fit the data to the model for the deterministic and stochastic case and the estimated basic reproduction number is R0≈1.1367. We show that the stochastic model provides a good fitting to the real data. We use the numerical approach to solve the stochastic system by presenting the results graphically. The sensitive parameters that significantly impact the model dynamics and reduce the number of infected cases in the future are shown graphically.
... Although the Centre for Disease Control and Prevention recommended limited testing for asymptomatic patients; it now recommends widespread testing, regardless of signs or symptoms to mitigate the transmission of SARS-CoV-2 [23]. Asymptomatic patients have the same infectivity as symptomatic ones [24]. Also, it is reported that asymptomatic patients have viral load similar to symptomatic patients [25]. ...
Background
Coronavirus disease 2019 (COVID-19) can present with pulmonary and non-pulmonary manifestations, or it may be asymptomatic. Asymptomatic patients have a major impact on transmission of the disease, and prediction of their outcome and prognosis is challenging. We aim to identify the predictors of intensive care unit (ICU) admission and mortality in hospitalized COVID-19 patients with initially asymptomatic presentation.
Methods
This was a prospective multicenter study using cohort data that included all admitted patients aged 21 years and above, with different clinical presentations other (than pulmonary manifestation) and were discovered to have COVID-19. Demographic data, clinical data and progression were reported. Univariate analysis and logistic regression analysis were performed to predict ICU admission and mortality during hospitalization.
Results
One hundred forty-nine consecutive patients, 92 (61.7% males) were included in our study, Median age (IQR) was 59.00 (43–69]. Only 1 patient (0.7%) had a contact with a confirmed case of COVID-19. 58 patients (39%) were admitted to ICU and 22 patients (14.8%) have died. High ferritin level (more than 422.5), low oxygen saturation (less than 93%), and in need of non-invasive ventilation (NIV) have 3.148, 8.159 and 26.456 times likelihood to be admitted to ICU, respectively. Patients with high CO-RADS, low oxygen saturation (less than 92.5%), and in need for mechanical ventilation (MV) have 82.8, 15.9, and 240.77 times likelihood to die, respectively.
Conclusion
Initially asymptomatic hospitalized patients with COVID-19 have a great impact on health system with high ICU admission and mortality rate. We identified the predictors that may help in early management and improving prognosis.
Trial registration
Trial was registered in Clinicaltrials.gov, registration number is NCT05298852 , 26 March 2022, retrospectively registered.
... This feature determines the high concealment of the spread of COVID-19, and leads to an increase in the difficulty of epidemic prevention and control. There have been a large number of research results on asymptomatic infections of new coronary pneumonia, including age distribution, average proportion, and transmission intensity [5,6,7]. In addition, some researchers have studied the spread of COVID-19 by establishing dynamic models including asymptomatic infections. ...
The COVID-19 epidemic has been spreading around the world for nearly three years, and asymptomatic infections have exacerbated the spread of the epidemic. To evaluate the role of asymptomatic infections in the spread of the epidemic, we develop mathematical models to assess the proportion of asymptomatic infections caused by different strains of the main covid-19 variants. The analysis shows that when the control reproduction number is less than 1, the disease-free equilibrium point of the model is globally asymptotically stable; and when the control reproduction number is greater than 1, the endemic equilibrium point exists and is unique, and is locally asymptotically stable. We fit the epidemic data in the four time periods corresponding to the selected 614G, Alpha, Delta and Omicron variants. The fitting results show that, from the comparison of the four time periods, the proportion of asymptomatic persons among the infected persons gradually increased. We also predict the peak time and peak value for the four time periods, and the results indicate that the transmission speed and transmission intensity of the variant strains increased to some extent. Finally, we discuss the impact of the detection ratio of symptomatic infections on the spread of the epidemic. The results show that with the increase of the detection ratio, the cumulative number of cases has dropped significantly, but the decline in the proportion of asymptomatic infections is not obvious. Therefore, in view of the hidden transmission of asymptomatic infections, the cooperation between various epidemic prevention and control policies is required to effectively curb the spread of the epidemic.
... One study suggests that asymptomatic cases can significantly infect lower proportions of other individuals compared to symptomatic cases [53]. Interestingly, it is assumed that the spread of COVID-19 by asymptomatic patients is likely to result in more asymptomatic infections, which has been backed up by the Diamond Princess cruise ship's outbreak [53,54]. Another study states that there are no evidence of infectious asymptomatic cases and the transmission of the virus to their close contacts. ...
Background: Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has become a major global concern. As of writing this manuscript, there are over 224 million cases diagnosed, and 4.5 million recorded deaths with the Coronavirus Disease 2019 (COVID-19).
Objectives: This article reviews the studies conducted on SARS-CoV-2 pathogenesis, transmission, and different clinical manifestations.
Methods: An extensive online search was conducted on PubMed and Google Scholar search engines. The following keywords and their combinations were used to complete this review: “SARS-CoV-2”, “COVID-19”, “virology”, “mechanism of action”, “transmission”, “clinical manifestations”, “laboratory findings”, and “comorbidities.”
Results: The SARS-CoV-2 spike glycoprotein recognizes the human angiotensin-converting enzyme 2 receptors, and through that, the virus can enter its host cell. The virus is mainly transmitted via respiratory and or airborne droplets. The severity of the COVID-19 clinical manifestations relies on the associated comorbidities and or old age, which ranges from little-to-no symptoms to severe and critical conditions. Fever, loss of appetite and or smell, fatigue, and dry cough are among the most reported symptoms. Underlying conditions may lead to severe or critical stages of COVID-19.
Conclusion: The SARS-CoV-2 nucleocapsid and receptor-binding domain could be two potential targets for future vaccines and drugs. It appears that the virus is adapting to each region’s specific environment; therefore, new endemic variants are forming.
... However, most infections are so called 'asymptomatic' and can transmit the virus to others [2]. Asymptomatic infections have the same infectivity as symptomatic infections [3,4]. Asymptomatic infections refer to patients without any apparent clinical symptoms or distinctive signs, but present with the positive detection of nucleic acid of SARS-CoV-2 in samples derived from the reverse the transcriptase-polymerase chain reaction (RT-PCR) [5]. ...
The new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus has high infectivity, often masked by asymptomatic carriers, which allows it to spread rapidly and become a pandemic. Attempts to slow the pandemic at this stage depend on the ability to unmask asymptomatic carriers. The rapid diagnosis of active coronavirus disease 2019 (COVID-19) infection is one of the cornerstones of pandemic control, as the nasal cavity is the main gateway for SARS-CoV-2 entry and altered sense of smell is a feature of the current virus. In the present study, we therefore tested the olfactory threshold coupled with heart–lung parameters in subjects undergoing traditional molecular testing, resulting in a significantly different score between asymptomatic subjects and healthy controls. In total, 82% of asymptomatic positives showed olfactory impairment; of these, 46% had severe hyposmia and 7% had anosmia, while in the control 9% had severe hyposmia and 0% had anosmia, respectively, which agrees with heart rate, breathing rate, and blood pressure parameter variations. The olfactory test coupled with physiological parameters may help to identify asymptomatic people. In conclusion, our results suggest that most asymptomatic individuals could be unmasked by mass olfactory rapid threshold screening and then referred to traditional slower diagnostic tests.
... However, when rerunning the analysis in STATA 16.1 based on data provided in the forest plot by the authors, the overall rate is 0.4% (95% CI 0-1.4%), suggesting on average 250 asymptomatic patients are needed to generate a single infection ( Figure 3). Reanalysis of secondary attack rates from truly asymptomatic and presymptomatic transmission [6][7][8]11,12,[14][15][16][17][18]. ...
Not all evidence is equal. Evidence-based public health and medicine emanate from the principle that there is a hierarchy of evidence, with systematic reviews and meta-analyses (SRMAs) being at the top, as the highest level of evidence. Despite this, it is common in literature to find SRMAs with methodological issues that can distort the results and can thus have serious public health or clinical implications. During the Coronavirus Disease 2019 (COVID-19) pandemic, the importance of evidence and the way in which evidence was produced was stress tested and revealed a wide array of methodological biases that might have led to misleading conclusions and recommendations. We provide a critical examination of methodological biases in selected SRMAs on COVID-19, which have been widely used to guide or justify some pharmaceutical and nonpharmaceutical interventions with high public health and clinical significance, such as mask wearing, asymptomatic transmission, and ivermectin. Through these selected examples, we highlight the need to address biases related to the methodological quality and relevance of study designs and effect size computations and considerations for critical appraisal of available data in the evidence synthesis process for better quality evidence. Such considerations help researchers and decision makers avoid misleading conclusions, while encouraging the provision of the best policy recommendations for individual and public health.
... In the SEIR model, the transmission rate from exposed to infected η is regarded as a constant and can be defined as η = 1 6 . According to the previous study carried out by (31), the infection rate of close contacts is 0.04. During the outbreak, nucleic acid tests will be carried out every 4 days, therefore, the confirmed time of COVID-19 is set to 4 (9,16). ...
With the improvement of treatment and prevention methods, many countries have the pandemic under control. Different from the globally large-scale outbreak of COVID-19 in 2020, now the outbreak in these countries shows new characteristics, which calls for an effective epidemic model to describe the transmission dynamics. Meeting this need, first, we extensively investigate the small-scale outbreaks in different provinces of China and use classic compartmental models, which have been widely used in predictions, to forecast the outbreaks. Additionally, we further propose a new version of cellular automata with a time matrix, to simulate outbreaks. Finally, the experimental results show that the proposed cellular automata could effectively simulate the small-scale outbreak of COVID-19, which provides insights into the transmission dynamics of COVID-19 in China and help countries with small-scale outbreaks to determine and implement effective intervention measures. The countries with relatively small populations will also get useful information about the epidemic from our research.
... Domenico et al. (2020) in setting up their model, based on Li et al. (2020) but for "undocumented" rather than "asymptomatic" patients. On the other hand (Chen et al. 2020), showed no statistically significant difference in the transmissibility of the virus between symptomatic and a/presymptomatic cases † † Estimates vary significantly as does the quality of the evidence. The range of the percentage of the asymptomatic individuals among those positively tested reported is 4.4-89% Model calibration Values of several model parameters remain uncertain, of which the transmission matrix β is virtually always one of them. ...
Running across the globe for nearly 2 years, the Covid-19 pandemic keeps demonstrating its strength. Despite a lot of understanding, uncertainty regarding the efficiency of interventions still persists. We developed an age-structured epidemic model parameterized with epidemiological and sociological data for the first Covid-19 wave in the Czech Republic and found that (1) starting the spring 2020 lockdown 4 days earlier might prevent half of the confirmed cases by the end of lockdown period, (2) personal protective measures such as face masks appear more effective than just a realized reduction in social contacts, (3) the strategy of sheltering just the elderly is not at all effective, and (4) leaving schools open is a risky strategy. Despite vaccination programs, evidence-based choice and timing of non-pharmaceutical interventions remains an effective weapon against the Covid-19 pandemic.
... SARS-CoV-2 can be highly contagious; asymptomatic patient may also transmit the virus. A study reported that COVID-19 transmission in asymptomatic patients and symptomatic patients were statistically similar [9]. The risk factors for COVID-19 include advanced age, diabetes, hypertension, obesity, and heart disease [10][11][12]. ...
The coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), appears to be diminishing in infectivity and hospitalizations in the United States and many parts of the world. This review will provide current information on the pathogenesis of SARS-CoV-2 and long haul COVID, emerging research on systemic complications, and antibody responses of vaccines and boosters.
... A point of attention that should be addressed by any health professional when employing our approach is the presence of co-infections. For instance, multiple cases of COVID-19 hospital cross-infections have been identified 55 . As we do not have data explicitly concerning co-infections, we cannot provide insights regarding the blood profiles that emerge in such situations which might confuse the model. ...
Background
The Complete Blood Count (CBC) is a commonly used low-cost test that measures white blood cells, red blood cells, and platelets in a person’s blood. It is a useful tool to support medical decisions, as intrinsic variations of each analyte bring relevant insights regarding potential diseases. In this study, we aimed at developing machine learning models for COVID-19 diagnosis through CBCs, unlocking the predictive power of non-linear relationships between multiple blood analytes.
Methods
We collected 809,254 CBCs and 1,088,385 RT-PCR tests for SARS-Cov-2, of which 21% (234,466) were positive, from 900,220 unique individuals. To properly screen COVID-19, we also collected 120,807 CBCs of 16,940 individuals who tested positive for other respiratory viruses. We proposed an ensemble procedure that combines machine learning models for different respiratory infections and analyzed the results in both the first and second waves of COVID-19 cases in Brazil.
Results
We obtain a high-performance AUROC of 90 + % for validations in both scenarios. We show that models built solely of SARS-Cov-2 data are biased, performing poorly in the presence of infections due to other RNA respiratory viruses.
Conclusions
We demonstrate the potential of a novel machine learning approach for COVID-19 diagnosis based on a CBC and show that aggregating information about other respiratory diseases was essential to guarantee robustness in the results. Given its versatile nature, low cost, and speed, we believe that our tool can be particularly useful in a variety of scenarios—both during the pandemic and after.
... En presencia de una mayor cantidad de síntomas informados, se observó una disminución de la probabilidad convivientes, fue superior a las reportadas en la mayor parte de la literatura internacional [10][11][12][13][14][22][23][24][25][26] . Es posible que el contexto de alta circulación viral, así como las prácticas sociales y culturales locales y estrategias de aislamiento menos eficaces en comparación a las empleadas en otros países podrían explicar, al menos en parte, las diferencias encontradas. ...
The objective was to describe the results of a surveillance strategy based on the use of SARS-CoV-2 rapid antigen detection tests. A retrospective cohort study was held between December 2020 and March 2021, which included suspected cases of COVID-19 evaluated by rapid antigen tests at a public hospital, with confirmatory molecular tests in negative cases. Positive cases and their close contacts were followed up by telephone. The scope, acceptability, follow-up coverage and positivity rate of the strategy were estimated, as well as indicators of viral transmissibility (probability of generating transmission, number of secondary infections generated, secondary attack rate, and overdispersion index). Its association with diagnostic tests results was analyzed by multivariate models. Of 1706 patients tested by rapid antigen tests, 526 were positive and 1180 were negative (65 tested positive by molecular tests); 579 confirmed cases could be contacted and 1669 close contacts were identified (85% of these contacts had full follow-up); 398 contacts tested positive during their quarantine (secondary attack rate of 27.9%). Of the 579 contacted cases, 205 (35%) reported symptomatic transmission, with an average of 0.91 secondary cases per infector. Transmission overdispersion was observed. Positive cases confirmed by rapid antigen tests had a higher chance of generating secondary cases, a higher number of secondary cases per infector and a higher secondary attack rate than those confirmed by molecular tests. In conclusion, the rapid antigen tests strategy showed high acceptability and coverage, and accelerated the diagnosis and identification of individuals with the highest contagiousness.
... This reproduction number is small and comparable to disease transmitted by droplets and different from that of viruses that are well spread via aerosols. 33,34 This may be linked with the number of SARS-CoV-2 virus necessary to cause an infection, which is still unknown. According to the study conducted in Caribbean region, airborne mode of transmissions through aerosols and medical procedures were reported. ...
This scientific review of mode of transmission of COVID-19 is to aid scientific community in generating hypothesis. The inadequate evidence on SARS-CoV-2 transmission has hindered the development of effective prevention strategy and resulted in continues pandemic of the COVID-19. Therefore, in this review, existing evidence is discussed, hypothesis is generated regarding COVID-19 mode of transmission, and recommendations are forwarded based on existing body of knowledge. Thus, two meters (2 m) physical distance is not completely safe even for large droplets and wearing a face mask is a key in the prevention of SARS-CoV-2 in public areas and confined space and public need to be vaccinated.
... According to the official announcement ( [16,[34][35][36][37]), the following variable values are determined. In the initial period of the epidemic, residents can move freely in the city, so we set NN � 2.7 for this period. ...
In late 2019, the COVID-19 pandemic began to spread over the world, causing millions of deaths. In the first few months of the pandemic, several countries (such as China) prevented the spread of the pandemic successfully. By contrast, the pandemic in many other countries was not controlled well. For example, India encountered a second serious outbreak of COVID-19 from April 2021 due to the poor resistance measures implemented by the government. To figure out the effective countermeasures to the pandemic, this research proposes a COVID-19 pandemic and its response system, which consists of the infection subsystem, the quarantine subsystem, and the medical subsystem. On this basis, an improved SEIR-SD model is established which is utilized to analyze the response measures to the pandemic quantitatively. This model successfully simulates the actual epidemic scenarios in Wuhan, which verifies its effectiveness. Afterward, the impact of hospital administration rate, quarantine rate, average contact number, and contact infection rate on the cumulative number of infections and deaths are analyzed by simulation. The results show that both the medical and administrative efforts, especially in the early stage of the epidemic, are significant in reducing the number of infections and shortening the epidemic period. In the medical aspect, the more stringent quarantine brings the earlier inflection point of the epidemic; more importantly, improving the treatment rate significantly reduces the scale of the epidemic. In the administrative aspect, enforcing individual protection and strict community closure can effectively cut off the transmission of the virus and curb the spread of the epidemic. Finally, this research proposes several practical suggestions in response to the COVID-19 pandemic. The main contribution of this research is that the effects of different response measures on the number of new infections daily and the cumulative number of deaths of a country or region in the COVID-19 pandemic are estimated quantitatively based on modeling and simulation.
... Also, many authors including Nishiura 29 and Mizumoto 30 conducted a statistical analysis of transmitting the COVID-19 disease by asymptomatic patients. Over a statistical study of 157 confirmed individuals and 30 asymptomatic infected persons, Chen et al. 31 reported that the differences in symptomatic and asymptomatic transmission are not statistically significant. However, in the study of Daihai et al. 32 , a statistically significant difference was found between the transmissions using the same data set. ...
Asymptomatic transmission of the coronavirus disease and the infected individual prediction has become very important in the COVID-19 outbreak study. The asymptomatic and symptomatic transmission studies are still ongoing to assess their impacts on disease monitoring and burden. However, there has been limited research on how asymptomatic and symptomatic transmissions together can affect the coronavirus disease outbreak. A mathematical model is therefore needed to be developed in order to assess the effect of these transmissions on the coronavirus disease dynamics. This paper develops a mathematical model concerning asymptomatic and symptomatic disease transmission processes in the COVID-19 outbreak. The model sensitivity has been analysed in terms of the variance of each parameter, and the local stability at two equilibrium points have been discussed in terms of the basic reproduction number (R0). It is found that the disease-free equilibrium gets stable for R0 < 1 whereas the endemic equilibrium becomes stable for R0 > 1 and unstable otherwise. The proportion of the effect of asymptomatic and symptomatic transmission rates on R0 is calculated to be approximately between 1 and 3. The results demonstrate that asymptomatic transmission has a significant impact compared to symptomatic transmission in the disease outbreak. Outcomes of this study will contribute to setting an effective control strategy for the COVID-19 outbreak.
... Similarly, 32.5% of the older population reported "Heart disease/ Myocardial infarction/ Congestive heart failure" in 2001, compared to only 11.9% of respondents in 2021. Moreover, the second phase of the study was completed in 2021, where the elderly, especially those with pre-existing conditions, are more sensitive to COVID-19 (Chen et al., 2020). Subsequent studies with a large sample size revealed that the condition is more prevalent in individuals over the age of 60 years than in those under the age of 60 (Liu et al., 2020). ...
The behavioural trends amongst the older Indian population have drastically changed in the past two decades. Given the existing load of diseases and lower levels of physical activity among India's elderly, it is widely recognised that older persons are more vulnerable. This paper aims to understand the decadal differences in their health status and leisure-time activities engagement, which can be attributed to various contexts in which geriatrics dwell. A cross-sectional study was carried out using individualised data collected with the help of a checklist/fixed-response questionnaire to determine the differences between the prevalence of ailments and the leisure-time activity engagement on two cross-sections, i.e., 2001 and 2021. Total 410 individuals over the age of 60 were included in the study during the course of its duration (200 males; 210 females). Descriptive and inferential analysis shows that time trends in ailments (10 out of 29) and leisure-time activities (17 out of 23) for samples A & B are significantly different at .05 and .01 levels of significance (denoted by p < .05 & .01). This study demonstrated that the two major dimensions of quality of life have improved with fewer ailments and more involvement in leisure-time activities. In conclusion, current demographic trends combined with rising urbanization and lifestyle changes have resulted in a slew of challenges for the elders in India. Although this study has mostly focused on the transitions in the elderly world, it is important to note that improvement in the quality of life of the elderly requires a comprehensive strategy and coordinated efforts from the health-related sectors.
RESUMO Introdução: A COVID-19, cujo agente causador é o coronavírus (SARS-CoV-2), atualmente se configura como uma pandemia. O curso clínico da doença tende a evoluir com sintomas respiratórios, sendo que o perfil de comorbidades e a faixa etária são os principais determinantes da evolução clínica dos indivíduos acometidos. Objetivo: Apresentar o perfil epidemiológico dos pacientes hospitalizados com COVID-19, no estado de Minas Gerais, no período entre janeiro de 2020 e maio de 2021. Metodologia: Trata-se de um estudo ecológico descritivo, com base em dados secundários, utilizando o Sistema de Informação Hospitalar do Sistema Único de Saúde brasileiro. Resultados: A prevalência de internações, a incidência acumulada, a necessidade de cuidado intensivo (UTI) e a taxa de mortalidade hospitalar foram maiores em idosos (≥ 60 anos), enquanto que, na população mais jovem (< 60 anos), foram encontradas as menores estimativas. Do total de hospitalizações e óbitos, tanto os homens foram os mais acometidos, como a cor/raça parda. Dos atendimentos, 99,53% foram de urgência, 71,16% não necessitaram de leitos de UTI. Houve um gasto total com as hospitalizações no valor de R$ 591.932.493,07, dos quais R$ 388.313.063,87 foram decorrente de internação em UTI. Conclusão: Percebe-se que a COVID-19 é mais preocupante no que se refere à população idosa e com comorbidades, enfatizando a necessidade do controle das doenças crônicas típicas do envelhecimento, assim como a necessidade de um envelhecimento saudável para que o curso clínico da doença evolua com menos probabilidade de complicações. ABSTRACT Introduction: COVID-19, which is caused by the coronavirus (SARS-CoV-2), is currently considered a as a pandemic disease. Its clinical course tends to evolve with respiratory symptoms, and the presence of comorbidities and age are the main determinants of clinical evolution in affected individuals. Objective: To present the epidemiological profile of patients hospitalized with COVID-19, in the state of Minas Gerais, Brazil, between January 2020 and May 2021. Methodology: This is a descriptive ecological study, based on secondary data, using the Hospital Information System of the Brazilian Unified Health System. Results: The prevalence of hospitalization, the cumulative incidence, the need for intensive care (ICU) and the hospital mortality rate were higher in older adults (≥ 60 years), while the lowest estimates were observed in the younger population (< 60 years). Considering the total number of hospitalizations and deaths, men and the brown color/race were most affected. As for the consultations, 99.53% were urgent, 71.16% did not require ICU beds, with the total expenditure on hospitalizations amounting to R$ 591,932,493.07, of which R$ 388,313,063.87 were related to ICU. Conclusion: COVID-19 is more concerning in relation to the older population and those with comorbidities, which emphasizes the need to control chronic diseases typical of aging, as well as the need for healthy aging. Thus, the clinical course of disease evolves with less probability of complications.
This study aims to optimize the COVID-19 screening strategies under China's dynamic zero-case policy through cost-effectiveness analysis. A total of 9 screening strategies with different screening frequencies and combinations of detection methods were designed. A stochastic agent-based model was used to simulate the progress of the COVID-19 outbreak in scenario I (close contacts were promptly quarantined) and scenario II (close contacts were not promptly quarantined). The primary outcomes included the number of infections, number of close contacts, number of deaths, the duration of the epidemic, and duration of movement restriction. Net monetary benefit (NMB) and the incremental cost-benefit ratio were used to compare the cost-effectiveness of different screening strategies. The results indicated that under China's COVID-19 dynamic zero-case policy, high-frequency screening can help contain the spread of the epidemic, reduce the size and burden of the epidemic, and is cost-effective. Mass antigen testing is not cost-effective compared with mass nucleic acid testing in the same screening frequency. It would be more cost-effective to use AT as a supplemental screening tool when NAT capacity is insufficient or when outbreaks are spreading very rapidly.
Objectives:
To identify the proportion of coronavirus disease 2019 (COVID-19) cases that occurred within households or buildings in New York City (NYC) beginning in March 2020 during the first stay-at-home order to determine transmission attributable to these settings and inform targeted prevention strategies.
Design:
The residential addresses of cases were geocoded (converting descriptive addresses to latitude and longitude coordinates) and used to identify clusters of cases residing in unique buildings based on building identification number (BIN), a unique building identifier. Household clusters were defined as 2 or more cases within 2 weeks of onset or diagnosis date in the same BIN with the same unit number, last name, or in a single-family home. Building clusters were defined as 3 or more cases with onset date or diagnosis date within 2 weeks in the same BIN who do not reside in the same household.
Setting:
NYC from March to December 2020.
Participants:
NYC residents with a positive SARS-CoV-2 nucleic acid amplification or antigen test result with a specimen collected during March 1, 2020, to December 31, 2020.
Main outcome measure:
The proportion of NYC COVID-19 cases in a household or building cluster.
Results:
The BIN analysis identified 65 343 building and household clusters: 17 139 (26%) building clusters and 48 204 (74%) household clusters. A substantial proportion of NYC COVID-19 cases (43%) were potentially attributable to household transmission in the first 9 months of the pandemic.
Conclusions:
Geocoded address matching assisted in identifying COVID-19 household clusters. Close contact transmission within a household or building cluster was found in 43% of noncongregate cases with a valid residential NYC address. The BIN analysis should be utilized to identify disease clustering for improved surveillance.
Introduction:
To compare the performance between the compartment model and the autoregressive integrated moving average (ARIMA) model that were applied to the prediction of new infections during the coronavirus disease 2019 (COVID-19) epidemic.
Methods:
The compartment model and the ARIMA model were established based on the daily cases of new infection reported in China from December 2, 2019 to April 8, 2020. The goodness of fit of the two models was compared using the coefficient of determination (R2).
Results:
The compartment model predicts that the number of new cases without a cordon sanitaire, i.e., a restriction of mobility to prevent spread of disease, will increase exponentially over 10 days starting from January 23, 2020, while the ARIMA model shows a linear increase. The calculated R2 values of the two models without cordon sanitaire were 0.990 and 0.981. The prediction results of the ARIMA model after February 2, 2020 have a large deviation. The R2 values of complete transmission process fit of the epidemic for the 2 models were 0.964 and 0.933, respectively.
Discussion:
The two models fit well at different stages of the epidemic. The predictions of compartment model were more in line with highly contagious transmission characteristics of COVID-19. The accuracy of recent historical data had a large impact on the predictions of the ARIMA model as compared to those of the compartment model.
Current persistent outbreak of COVID-19 is triggering a series of collective responses to avoid infection. To further clarify the impact mechanism of adaptive protection behavior and vaccination, we developed a new transmission model via a delay differential system, which parameterized the roles of adaptive behaviors and vaccination, and allowed to simulate the dynamic infection process among people. By validating the model with surveillance data during March 2020 and October 2021 in America, India, South Africa, Philippines, Brazil, UK, Spain and Germany, we quantified the protection effect of adaptive behaviors by different forms of activity function. The modeling results indicated that (1) the adaptive activity function can be used as a good indicator for fitting the intervention outcome, which exhibited short-term awareness in these countries, and it could reduce the total human infections by 3.68, 26.16, 15.23, 4.23, 7.26, 1.65, 5.51 and 7.07 times, compared with the reporting; (2) for complete prevention, the average proportions of people with immunity should be larger than 90%, 92%, 86%, 71%, 92%, 84%, 82% and 76% with adaptive protection behaviors, or 91%, 97%, 94%, 77%, 92%, 88%, 85% and 90% without protection behaviors; and (3) the required proportion of humans being vaccinated is a sub-linear decreasing function of vaccine efficiency, with small heterogeneity in different countries. This manuscript was submitted as part of a theme issue on “Modelling COVID-19 and Preparedness for Future Pandemics”.
Dynamic modeling of infectious disease can simulate transmission processes of COVID-19, a newly been found infectious respiratory disease that has a substantial impact on both people's health and social development, and therefore plays an important role in the prediction and prevention of epidemics. Although there are many models that can accurately represent the number of infected patients, the influence of human factors on the transmission of the virus has not been fully investigated. Here, by considering the influence of policies on restricting contact between people, we modified the SEIR infectious disease model and developed a new model called the Quarantine-considering SEIR model (hereafter referred to as Q-SEIR), combining with dynamic parameter, contact rate, obtained by machine learning method, we can represent the effects of human movement and contact behavior during the epidemic.
The experimental results show that this method can effectively represent the effect of patterns of population activity on the development of the epidemic. On one hand, our research results provide guidance for the government before issuing measures to restrict the movement and socialization of people; and on the other hand, our findings help identify the development stage of the epidemic more clearly for the public as well as provide information for citizens’ travel decisions.
We propose two different mathematical models to study the effect of immigration on the COVID-19 pandemic. The first model does not consider immigration, whereas the second one does. Both mathematical models consider five different subpopulations: susceptible, exposed, infected, asymptomatic carriers, and recovered. We find the basic reproduction number R0 using the next-generation matrix method for the mathematical model without immigration. This threshold parameter is paramount because it allows us to characterize the evolution of the disease and identify what parameters substantially affect the COVID-19 pandemic outcome. We focus on the Venezuelan scenario, where immigration and emigration have been important over recent years, particularly during the pandemic. We show that the estimation of the transmission rates of the SARS-CoV-2 are affected when the immigration of infected people is considered. This has an important consequence from a public health perspective because if the basic reproduction number is less than unity, we can expect that the SARS-CoV-2 would disappear. Thus, if the basic reproduction number is slightly above one, we can predict that some mild non-pharmaceutical interventions would be enough to decrease the number of infected people. The results show that the dynamics of the spread of SARS-CoV-2 through the population must consider immigration to obtain better insight into the outcomes and create awareness in the population regarding the population flow.
Coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was first reported December 31, 2019, to the China Ministry of Health and the World Health Organization (WHO). It started in Wuhan, China, and is highly contagious. The spread was rapid, and it was declared a global emergency on January 30, 2020 and global pandemic on March 11, 2020. SARS-CoV-2 transmits via droplet, aerosol, oral-fecal routes, as well as contact with contaminated surfaces and oral fluids. Dentists and healthcare professionals are at risk of exposure to SARS-CoV-2 during daily patient care. Dental and medical offices are at risk for patient and healthcare provider cross infection. Thus, personal protective equipment (PPE) like masks, face shields, and gowns, as well as hand washing and pre-treatment mouth rinsing are adopted in the dental and medical facilities to curb the spread of COVID-19
Background
Non-pharmaceutical interventions (NPIs) used to limit SARS-CoV-2 transmission vary in their feasibility, appropriateness and effectiveness in different contexts. In Bangladesh a national lockdown implemented in March 2020 exacerbated poverty and was untenable long-term. A resurgence in 2021 warranted renewed NPIs. We sought to identify NPIs that were feasible in this context and explore potential synergies between interventions.
Methods
We developed an SEIR model for Dhaka District, parameterised from literature values and calibrated to data from Bangladesh. We discussed scenarios and parameterisations with policymakers with the aid of an interactive app. These discussions guided modelling of lockdown and two post-lockdown measures considered feasible to deliver; symptoms-based household quarantining and compulsory mask-wearing. We compared NPI scenarios on deaths, hospitalisations relative to capacity, working days lost, and cost-effectiveness.
Results
Lockdowns alone were predicted to delay the first epidemic peak but could not prevent overwhelming of the health service and were costly in lost working days. Impacts of post-lockdown interventions depended heavily on compliance. Assuming 80% compliance, symptoms-based household quarantining alone could not prevent hospitalisations exceeding capacity, whilst mask-wearing prevented overwhelming health services and was cost-effective given masks of high filtration efficiency. Combining masks with quarantine increased their impact. Recalibration to surging cases in 2021 suggested potential for a further wave in 2021, dependent on uncertainties in case reporting and immunity.
Conclusions
Masks and symptoms-based household quarantining synergistically prevent transmission, and are cost-effective in Bangladesh. Our interactive app was valuable in supporting decision-making, with mask-wearing being mandated early, and community teams being deployed to support quarantining across Dhaka. These measures likely contributed to averting the worst public health impacts, but delivering an effective response with consistent compliance across the population has been challenging. In the event of a further resurgence, concurrent messaging to increase compliance with both mask-wearing and quarantine is recommended.
Although all cities in China have promulgated public transportation control measures to choke off the spread of COVID-19, it also has brought severe changes to low-income individuals’ bus traveling. However, the study focusing on satisfaction differences in bus traveling before and after COVID-19 is far under-researched, this paper therefore explored satisfaction differences among low-income individuals under socioeconomic attributes, traveling attributes, and psychological attributes by using the data consist of interviews addressed to 930 individuals in Taiyuan, China. Furthermore, the relationship between satisfaction levels and modes of traveling alone and traveling with companions by bus has also been deeply analyzed to reduce single-person driving problem. As a result, many exciting phenomena were discovered: the significant factors affecting low-income individuals’ satisfaction occur “shift” on a large scale after COVID-19; risk concern has a significant positive impact on risk perception, but risk concern and risk perception have only a minor impact on satisfaction before and after COVID-19; it was found that there is a significant relationship between satisfaction levels and modes of traveling alone and traveling with companions by bus. Understanding them can be a reference for improving the travel environment between low-income individuals.
Risk assessment of the intra-city spatio-temporal spreading of COVID-19 is important for providing location-based precise intervention measures, especially when the epidemic occurred in the densely populated and high mobile public places. The individual-based simulation has been proven to be an effective method for the risk assessment. However, the acquisition of individual-level mobility data is limited. This study used publicly available datasets to approximate dynamic intra-city travel flows by a spatio-temporal gravity model. On this basis, an individual-based epidemic model integrating agent-based model with the susceptible-exposed-infectious-removed (SEIR) model was proposed and the intra-city spatio-temporal spreading process of COVID-19 in eleven public places in Guangzhou China were explored. The results indicated that the accuracy of dynamic intra-city travel flows estimated by available big data and gravity model is acceptable. The spatio-temporal simulation method well presented the process of COVID-19 epidemic. Four kinds of spatial-temporal transmission patterns were identified and the pattern was highly dependent on the urban spatial structure and location. It indicated that location-based precise intervention measures should be implemented according to different regions. The approach of this research can be used by policy-makers to make rapid and accurate risk assessments and to implement intervention measures ahead of epidemic outbreaks.
SARS-CoV-2 has caused severe respiratory illnesses and deaths since late 2019 and spreads globally. While asymptomatic cases play a crucial role in transmitting COVID-19, they do not contribute to the observed prevalence, which drives behavior change during the pandemic. This study aims to identify the effect of the proportion of asymptomatic infections on the magnitude of an epidemic under behavior change scenarios by developing a compartmental mathematical model. In this interest, we discuss three different behavior change cases separately: constant behavior change, instantaneous behavior change response to the disease’s perceived prevalence, and piecewise constant behavior change response to government policies. Our results imply that the proportion of asymptomatic infections which maximizes the spread of the epidemic depends on the nature of the dominant force driving behavior changes.
As the COVID-19 vaccination has been quickly rolling out around the globe, the evaluation of the effects of vaccinating populations for the safe reopening of schools has become a focal point for educators, decision-makers, and the general public. Within this context, we develop a contact network agent-based model (CN-ABM) to simulate on-campus disease transmission scenarios. The CN-ABM establishes contact networks for agents based on their daily activity patterns, evaluates the agents’ health status change in different activity environments, and then simulates the epidemic curve. By applying the model to a real-world campus environment, we identify how different community risk levels, teaching modalities, and vaccination rates would shape the epidemic curve. The results show that without vaccination, retaining under 50% of on-campus students can largely flatten the curve, and having 25% on-campus students can achieve the best result (peak value < 1%). With vaccination, having a maximum of 75% on-campus students and at least a 45% vaccination rate can suppress the curve, and a 65% vaccination rate can achieve the best result. The developed CN-ABM can be employed to assist local government and school officials with developing proactive intervention strategies to safely reopen schools.
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