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In many infectious diseases, an unknown fraction of infections produce symptoms mild enough to go unrecorded, a fact that can seriously compromise the interpretation of epidemiological records. This is true for cholera, a pandemic bacterial disease, where estimates of the ratio of asymptomatic to symptomatic infections have ranged from 3 to 100 (re...
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The causative agent of cholera, Vibrio cholerae, has been shown to be autochthonous to riverine, estuarine, and coastal waters along with its host, the copepod, a significant member of the zooplankton community. Temperature, salinity, rainfall and plankton have proven to be important factors in the ecology of V. cholerae, influencing the transmissi...
To study epidemiologic characteristics of a cholera outbreak involving mainly Myanmar migrants living in overcrowded conditions with poor sanitation in a Thai-Myanmar border district, in 2007.
Both passive and active case surveillances were carried out in Mae Sot District, Tak Province since the beginning of the outbreak. Samples of various types o...
Cholera, an acute diarrheal infectious disease caused by the bacterium Vibrio cholerae, displays a seasonal pattern that still remains poorly understood. Two epidemic peaks per year is the typical pattern in endemic areas in Bangladesh and former Bengal, with a decline in the summer during the monsoons, but only one peak coincident with the rainy s...
Thirty single-nucleotide polymorphisms were used to track the spread of the seventh pandemic caused by Vibrio cholerae. Isolates from the 1991 epidemic in Latin America shared a profile with 1970s isolates from Africa, suggesting a possible origin in Africa. Data also showed that the observed genotypes spread easily and widely.
Citations
... Fortunately, the widespread availability of highperformance computing and the development of sophisticated nonlinear optimization algorithms have made it possible to fit a vast range of nonlinear ecological models to data [2]. Many applications of model-fitting have focused on human diseases, for which an extensive knowledge base makes it possible to write down at least basic models using only information from the literature [3]. A very large set of ecological problems, however, instead involve natural systems about which so little is known that there is often a great deal of uncertainty about the model structure [1]. ...
... In spite of the availability of sophisticated optimization algorithms and high-performance computing, parameter estimation and inference (and inverse problems in general) in non-linear dynamical systems remain a challenging problem [28]. Many of the existing parameter estimation methods in practice, such as non-linear least squares 3 . and likelihood-based methods, still use optimization (cost) functions which are based on comparisons of data to the solution of the system. ...
Species subject to predation and environmental threats commonly exhibit variable periods of population boom and bust over long timescales. Understanding and predicting such behavior, especially given the inherent heterogeneity and stochasticity of exogenous driving factors over short timescales, is an ongoing challenge. A modeling paradigm gaining popularity in the ecological sciences for such multi-scale effects is to couple short-term continuous dynamics to long-term discrete updates. We develop a data-driven method utilizing weak-form equation learning to extract such hybrid governing equations for population dynamics and to estimate the requisite parameters using sparse intermittent measurements of the discrete and continuous variables. The method produces a set of short-term continuous dynamical system equations parametrized by long-term variables, and long-term discrete equations parametrized by short-term variables, allowing direct assessment of interdependencies between the two time scales. We demonstrate the utility of the method on a variety of ecological scenarios and provide extensive tests using models previously derived for epizootics experienced by the North American spongy moth (Lymantria dispar dispar).
... To better understand the epidemiology of cholera and to predict the impact of interventions in the future, researcher build mathematical models as tools complementary to epidemiology and statistical analysis. However, many dynamics of cholera are based on SIR models (Brauer, Shuai, & Driessche, 2013;King, Ionides, Pascual, & Bouma, 2008;Phan, Tian, & Wang, 2021;Stephen & Nkuba, 2015;Tian, Liao, & Wang, 2021). In 2013, M. C. Eisenberg et al. used rainfall in a SIR model of cholera coupled the V. cholerae in the environment (Eisenberg, Kujbida, Tuite, Fisman, & Tien, 2013). ...
... His work indeed underscores the need of attention from the urgent need for sewage and water management infrastructure. Even if these models take into account free bacteria V. cholerae in the environment, experience with COVID-19 shows that it is important to differentiate between detected and undetected cases (which in the case of cholera are the asymptomatic infectious (Isaac, 2014;King et al., 2008)). In this way, Albalawi et al. (Albalawi et al., 2023) included in 2023 quarantine individuals in their mathematical model that could determine the asymptomatic cases registered by the health authority. ...
This paper deals with the problem of the prediction and control of cholera outbreak using real data of Cameroon. We first develop and analyze a deterministic model with seasonality for the cholera, the novelty of which lies in the incorporation of undetected cases. We present the basic properties of the model and compute two explicit threshold parameters R¯0 and R_0 that bound the effective reproduction number R0, from below and above, that is R_0≤R0≤R¯0. We prove that cholera tends to disappear when R¯0≤1, while when R_0>1, cholera persists uniformly within the population. After, assuming that the cholera transmission rates and the proportions of newly symptomatic are unknown, we develop the EnKf approach to estimate unmeasurable state variables and these unknown parameters using real data of cholera from 2014 to 2022 in Cameroon. We use this result to estimate the upper and lower bound of the effective reproduction number and reconstructed active asymptomatic and symptomatic cholera cases in Cameroon, and give a short-term forecasts of cholera in Cameroon until 2024. Numerical simulations show that (i) the transmission rate from free Vibrio cholerae in the environment is more important than the human transmission and begin to be high few week after May and in October, (ii) 90% of newly cholera infected cases that present the symptoms of cholera are not diagnosed and (iii) 60.36% of asymptomatic are detected at 14% and 86% of them recover naturally. The future trends reveals that an outbreak appeared from July to November 2023 with the number of cases reported monthly peaked in October 2023. An impulsive control strategy is incorporated in the model with the aim to avoid or prevent the cholera outbreak. In the first year of monitoring, we observed a reduction of more than 75% of incidences and the disappearance of the peaks when no control are available in Cameroon. A second monitoring of control led to a further reduction of around 60% of incidences the following year, showing how impulse control could be an effective means of eradicating cholera.
... Our modelling choices are aimed at simplicity and driven by the overall goal of checking the consistency between these data sources. For instance, we deliberately take an agnostic stance on the open questions related to the role of the environment or details of bacterial dynamics: while several previous studies explicitly included the environmental compartment [17][18][19][20][21] leading to a larger number of model parameters, we chose to model cholera dynamics as an effective transmission process which includes a periodic functional dependence on seasonality, similarly to the approach of Peak et al. [22]. To account for discreteness in observed cases, we propose a novel sampling model which relates the continuous model with the discrete observed case counts. ...
... Many cholera models in the literature include an environmental compartment [17][18][19][20][21]. Such an environmental compartment is typically introduced to explicitly model the transmission of infection through a water source, and additionally describes the evolution of bacteria in a water source with temperature-dependent dynamics. ...
Cholera continues to be a global health threat. Understanding how cholera spreads between locations is fundamental to the rational, evidence-based design of intervention and control efforts. Traditionally, cholera transmission models have used cholera case-count data. More recently, whole-genome sequence data have qualitatively described cholera transmission. Integrating these data streams may provide much more accurate models of cholera spread; however, no systematic analyses have been performed so far to compare traditional case-count models to the phylodynamic models from genomic data for cholera transmission. Here, we use high-fidelity case-count and whole-genome sequencing data from the 1991 to 1998 cholera epidemic in Argentina to directly compare the epidemiological model parameters estimated from these two data sources. We find that phylodynamic methods applied to cholera genomics data provide comparable estimates that are in line with established methods. Our methodology represents a critical step in building a framework for integrating case-count and genomic data sources for cholera epidemiology and other bacterial pathogens.
... Several countries have devised national cholera control plans that rely on passive clinical surveillance and have bold targets, often including elimination of the disease by 2030. Our results affirm previous modeling results that inapparent infections may be key to understanding V. cholerae O1 transmission in endemic areas 32 . This implies that the absence of cases may not mean absence of transmission, which must be considered when approaching elimination. ...
Our understanding of cholera transmission and burden largely relies on clinic-based surveillance, which can obscure trends, bias burden estimates and limit the impact of targeted cholera-prevention measures. Serological surveillance provides a complementary approach to monitoring infections, although the link between serologically derived infections and medically attended disease incidence—shaped by immunological, behavioral and clinical factors—remains poorly understood. We unravel this cascade in a cholera-endemic Bangladeshi community by integrating clinic-based surveillance, healthcare-seeking and longitudinal serological data through statistical modeling. Combining the serological trajectories with a reconstructed incidence timeline of symptomatic cholera, we estimated an annual Vibrio cholerae O1 infection incidence rate of 535 per 1,000 population (95% credible interval 514–556), with incidence increasing by age group. Clinic-based surveillance alone underestimated the number of infections and reported cases were not consistently correlated with infection timing. Of the infections, 4 in 3,280 resulted in symptoms, only 1 of which was reported through the surveillance system. These results impart insights into cholera transmission dynamics and burden in the epicenter of the seventh cholera pandemic, where >50% of our study population had an annual V. cholerae O1 infection, and emphasize the potential for a biased view of disease burden and infection risk when depending solely on clinical surveillance data.
... To estimate parameters, we implemented the above model as a stochastic model and calibrated it using an extended Kalman filter. The Kalman filter and extended filtering methods have been often used for calibrating a dynamic model with epidemiological surveillance data such as the daily number of reported cases [27,28]. In this study, we employed the filtering method to fit the transmission model to the observed daily cases, virus concentrations in wastewater, or both, by incorporating the observation errors. ...
Background
Wastewater surveillance has expanded globally as a means to monitor spread of infectious diseases. An inherent challenge is substantial noise and bias in wastewater data because of the sampling and quantification process, limiting the applicability of wastewater surveillance as a monitoring tool.
Aim
To present an analytical framework for capturing the growth trend of circulating infections from wastewater data and conducting scenario analyses to guide policy decisions.
Methods
We developed a mathematical model for translating the observed SARS-CoV-2 viral load in wastewater into effective reproduction numbers. We used an extended Kalman filter to infer underlying transmissions by smoothing out observational noise. We also illustrated the impact of different countermeasures such as expanded vaccinations and non-pharmaceutical interventions on the projected number of cases using three study areas in Japan during 2021–22 as an example.
Results
Observed notified cases were matched with the range of cases estimated by our approach with wastewater data only, across different study areas and virus quantification methods, especially when the disease prevalence was high. Estimated reproduction numbers derived from wastewater data were consistent with notification-based reproduction numbers. Our projections showed that a 10–20% increase in vaccination coverage or a 10% reduction in contact rate may suffice to initiate a declining trend in study areas.
Conclusion
Our study demonstrates how wastewater data can be used to track reproduction numbers and perform scenario modelling to inform policy decisions. The proposed framework complements conventional clinical surveillance, especially when reliable and timely epidemiological data are not available.
... Most cholera infections are thought to be asymptomatic or subclinical. They may not be of clinical relevance but the infected may still transmit the bacteria and acquire immunity, which can have important impacts on the epidemiological dynamics of the current or future outbreaks [11][12][13][14]. Importantly, the proportion of the population with full or partial immunity can thus not be determined from clinical surveillance alone but is of crucial importance to gauge the future course of an outbreak or to plan vaccination campaigns. ...
... is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint extremely common. Despite the scientific consensus that the number of asymptomatic or mild infections is many times higher than the number of clinically relevant infections, estimates have varied widely (factor 2 to 100), likely as a result of variable case definitions, individual infection histories, different V cholerae strains and host factors (Supplementary Material) [11,13,[20][21][22][23][24][25][26][27]. Being able to translate between the number of cases observed at health facilities and the true number of infections in the community, or vice-versa, could help improve the public health utility of serosurveillance data and strengthen our understanding of cholera epidemiology and immunity. ...
... Our estimates of the ratio of infections to reported clinical cholera cases are at the lower end of those previously reported, which likely reflects that this population had no previous exposure to the bacteria, but could also reflect differences in host factors (e.g., undernutrition) and exposure routes [11][12][13]20,21,[24][25][26][27]. Our estimated number of infections among young children nearly matches the numbers of reported suspected cholera cases, this either implies that there were almost no infections in this age group that did not results in medically-attended disease, or more realistically that unreported infections got compensated by the poor specificity of the suspected cholera case definition, especially in young children, where other etiologies frequently lead to similar symptoms. ...
Most infections with pandemic Vibrio cholerae are thought to result in subclinical disease and are not captured by surveillance. Previous estimates of the ratio of infections to clinical cases have varied widely (2 to 100). Understanding cholera epidemiology and immunity relies on the ability to translate between numbers of clinical cases and the underlying number of infections in the population. We estimated the infection incidence during the first months of an outbreak in a cholera-naive population using a Bayesian vibriocidal antibody titer decay model combining measurements from a representative serosurvey and clinical surveillance data. 3,880 suspected cases were reported in Grande Saline, Haiti, between 20 October 2010 and 6 April 2011 (clinical attack rate 18.4%). We found that more than 52.6% (95% Credible Interval (CrI) 49.4-55.7) of the population ≥2 years showed serologic evidence of infection, with a lower infection rate among children aged 2-4 years (35.5%; 95%CrI 24.2-51.6) compared with people ≥5 years (53.1%; 95%CrI 49.4-56.4). This estimated infection rate, nearly three times the clinical attack rate, with underdetection mainly seen in those ≥5 years, has likely impacted subsequent outbreak dynamics. Our findings show how seroincidence estimates improve understanding of links between cholera burden, transmission dynamics and immunity.
Key Results
We combine serological and clinical cholera incidence in an outbreak in a naive population in Grande Saline, Haiti.
The rate of infection with Vibrio cholerae was several times the clinical attack rate.
Half of the population ≥2 years showed serological evidence of infection.
For every reported clinical case ≥5 years old, 3.2 (95% CrI 3.0-3.4) people were infected.
Children 2-4 years old had a lower infection rate, which was not significantly different from the clinical attack rate.
... Often, the identification of cholera is very difficult as most people infected are asymptomatic or exhibit mild symptoms which can be mistaken for diarrhoea (WHO, 2021). According to King et al. (2008), mild or asymptomatic cholera cases affect "the interpretation of epidemiological records." ...
Cholera is a highly infectious disease with the ability to cause death within hours; an outbreak of epidemic forms of cholera is widely treated as a public health emergency. Ghana is considered a cholera hotspot because the major risk factor of cholera, poor sanitation, is ever-present in most parts of the country. Data were gathered in 2021 from the archives, oral interviews, and literary sources to explore how cholera was understood and treated in the Asante Region of Ghana, with a primary focus on Ayigya Zongo in the city of Kumase. Findings revealed that most interviewees were aware of what cholera is and to a large extent the means of prevention, but socio-economic conditions may force a neglect of facts. Proper sanitation, drinking safe water, and eating clean and healthy foods are among the basic means of preventing the disease, and may also prevent other sanitary-related diseases including other diarrhoeal diseases and typhoid fever. A success story in
Ayigya Zongo could have further implication for West-Africa, Ghana and Asante in particular.
... The epidemiology of some infectious disease has been studied extensively using mathematical models [17][18][19][20][21][22][23][24][25][26]32,35]. In this study, we utilize a mathematical model to ascertain the influence of control measures in reducing typhoid fever in a diverse socio-economic community. ...
Typhoid fever is an infectious disease that affects humanity worldwide particularly in the lower socio-economic communities where many individuals are exposed to a dirty environment and unclean food. A mathematical model is formulated to analyze the impact of control measures such as vaccination of susceptible humans, treatment of infected humans and sanitation in the different socio-economic communities. The model assumed that the population comprises of two socio-economic classes. The essential dynamical system analysis of our model was appropriately carried out. The impact of the control measures was analyzed, and the optimal control theory was applied on the control model to explore the impact of the different control measures. Numerical simulation of the models and the optimal controls were carried out and results obtained indicates that the overall combination of the control measures eradicates Typhoid fever in the population but the controls are more optimal in the higher socio-economic communities.
... thus, we use A k ðt j Þ � Nð� k t j � � ;d 2 Þ; j ¼ 1; :::; n for the parameter estimation (see [35]). To this extent, we add noise for each of the variables A k (t j ) with k = 1, . . ...
This paper studies the updated estimation method for estimating the transmission rate changes over time. The models for the population dynamics under SEIR epidemic models with stochastic perturbations are analysed the dynamics of the COVID-19 pandemic in Bogotá, Colombia. We performed computational experiments to interpret COVID-19 dynamics using actual data for the proposed models. We estimate the model parameters and updated their estimates for reported infected and recovered data.
... The copyright holder for this preprint this version posted July 23, 2023. 30 . This implies that the absence of cases may not mean absence of transmission, which must be taken into account when approaching elimination. ...
Our understanding of cholera transmission and burden largely rely on clinic-based surveillance, which can obscure trends, bias burden estimates and limit the impact of targeted cholera-prevention measures. Serologic surveillance provides a complementary approach to monitoring infections, though the link between serologically-derived infections and medically-attended disease, shaped by immunological, behavioral, and clinical factors, remains poorly understood. We unravel this cascade in a cholera-endemic Bangladeshi community by integrating clinic-based surveillance, healthcare seeking, and longitudinal serological data through statistical modeling. We found >50% of the study population had a V. cholerae O1 infection annually, and infection timing was not consistently correlated with reported cases. Four in 2,340 infections resulted in symptoms, only one of which was reported through the surveillance system. These results provide new insights into cholera transmission dynamics and burden in the epicenter of the 7th cholera pandemic and provide a framework to synthesize serological and clinical surveillance data.
