Mathematical modelling and numerical simulations of the influence of hygiene and seasons on the spread of cholera

Dangbé, Ezekiel; Damakoa, Irépran; Perasso, Antoine; Békollè, David

doi:10.1016/j.mbs.2017.12.004

Cited by 26 publications

(11 citation statements)

References 39 publications

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“…More sophisticated SEIR modeling concepts have been proposed with varying constraints of population structure [86], socio-economic factors [86,87], and other critical factors relevant to the transmission dynamics of cholera. Primarily, mathematical sophistication introduced into a SEIR model aims to address the environmental, biological, and behavioral stochasticity inherent in the mechanism of cholera transmission [56] However, in some cases, rigorous mathematical complexity may impart problems in evaluating the success of intervention strategies and in assessing the effectiveness of behavioral changes in the human population [80].…”

Section: Trigger and Transmission Components For Prediction Of Choleramentioning

confidence: 99%

“…While these methods help to improve the prediction of cholera transmission within well-mixed populations, they fail to capture cholera modes of infection via indirect routes, such as pathogen movement via the environment, or heterogeneities relevant to disease transmission. Interaction between environment and humans is of paramount importance for predictive modeling of cholera [87]. Traditional SEIR models are less successful in dealing with indirect modes of cholera transmission, most likely explaining why they are successful in predicting highly infectious human pathogen spread via direct human-tohuman contact (e.g., for viruses causing influenza and coronavirus disease 2019, COVID-19) compared to cholera, where indirect transmission plays a more important role [80].…”

Section: Trigger and Transmission Components For Prediction Of Choleramentioning

confidence: 99%

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A Review of the Environmental Trigger and Transmission Components for Prediction of Cholera

et al. 2021

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Climate variables influence the occurrence, growth, and distribution of Vibrio cholerae in the aquatic environment. Together with socio-economic factors, these variables affect the incidence and intensity of cholera outbreaks. The current pandemic of cholera began in the 1960s, and millions of cholera cases are reported each year globally. Hence, cholera remains a significant health challenge, notably where human vulnerability intersects with changes in hydrological and environmental processes. Cholera outbreaks may be epidemic or endemic, the mode of which is governed by trigger and transmission components that control the outbreak and spread of the disease, respectively. Traditional cholera risk assessment models, namely compartmental susceptible-exposed-infected-recovered (SEIR) type models, have been used to determine the predictive spread of cholera through the fecal–oral route in human populations. However, these models often fail to capture modes of infection via indirect routes, such as pathogen movement in the environment and heterogeneities relevant to disease transmission. Conversely, other models that rely solely on variability of selected environmental factors (i.e., examine only triggers) have accomplished real-time outbreak prediction but fail to capture the transmission of cholera within impacted populations. Since the mode of cholera outbreaks can transition from epidemic to endemic, a comprehensive transmission model is needed to achieve timely and reliable prediction with respect to quantitative environmental risk. Here, we discuss progression of the trigger module associated with both epidemic and endemic cholera, in the context of the autochthonous aquatic nature of the causative agent of cholera, V. cholerae, as well as disease prediction.

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Section: Trigger and Transmission Components For Prediction Of Choleramentioning

confidence: 99%

Section: Trigger and Transmission Components For Prediction Of Choleramentioning

confidence: 99%

A Review of the Environmental Trigger and Transmission Components for Prediction of Cholera

et al. 2021

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“…Moreover, the endemic global stability was investigated using three techniques: monotonic dynamical systems, geometric approach, and Lyapunov functions, up to July 17, 2020. Another study is that by Dangbé et al [3] which identified climatic factors and human behavior parameters that minimize the spread of cholera tangibly or intangibly. The equilibria stabilities of ordinary differential equations in the proposed model were investigated.…”

Section: Introductionmentioning

confidence: 99%

A dynamic optimal control model for COVID-19 and cholera co-infection in Yemen

2021

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In this work, we propose a new dynamic mathematical model framework governed by a system of differential equations that integrates both COVID-19 and cholera outbreaks. The estimations of the model parameters are based on the outbreaks of COVID-19 and cholera in Yemen from January 1, 2020 to May 30, 2020. Moreover, we present an optimal control model for minimizing both the number of infected people and the cost associated with each control. Four preventive measures are to be taken to control the outbreaks: social distancing, lockdown, the number of tests, and the number of chlorine water tablets (CWTs). Under the current conditions and resources available in Yemen, various policies are simulated to evaluate the optimal policy. The results obtained confirm that the policy of providing resources for the distribution of CWTs, providing sufficient resources for testing with an average social distancing, and quarantining of infected individuals has significant effects on flattening the epidemic curves.

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“…This is because spatial and temporal heterogeneities (involving distinctions in ecological and geographical environments, population characteristics, and socioeconomic structures) cause variations in the disease contact rates, human activity levels, bacterial dispersal and degradation, etc., which in turn strongly affect cholera dynamics. First, the need for two infectious classes was emphasized by making a distinction between asymptomatic (mild/inapparent) and symptomatic (severe) infections in infected individuals [11,20,24]. Secondly, cholera is a seasonal disease in many endemic places and infection peaks often occur annually in the rainy or monsoon season [34].…”

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confidence: 99%

“…Secondly, cholera is a seasonal disease in many endemic places and infection peaks often occur annually in the rainy or monsoon season [34]. Several studies have been devoted to seasonal variation in cholera dynamics [9,12,11,22,27]. For instance, Codeço [9] conducted simple numerical simulation to study cholera dynamics in three scenarios with time-periodic parameters.…”

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confidence: 99%

A general multipatch cholera model in periodic environments

Wang¹

2022

DCDS-B

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This paper is devoted to a general multipatch cholera epidemic model to investigate disease dynamics in a periodic environment. The basic reproduction number R 0 is introduced and a threshold type of result is established in terms of R 0 . Specifically, we show that when R 0 < 1, the disease-free steady state is globally attractive if either immigration of hosts is homogeneous or immunity loss of human hosts can be neglected; when R 0 > 1, the disease is uniformly persistent and our system admits at least one positive periodic solution. Numerical simulations are carried out to illustrate the impact of asymptotic infections and population dispersal on the spread of cholera. Our result indicates that (a) neglecting asymptotic infections may underestimate the risk of infection; (b) travel can help the disease to become persistent (resp. eradicated) in the network, even though the disease dies out (resp. persists) in each isolated patch.

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Mathematical modelling and numerical simulations of the influence of hygiene and seasons on the spread of cholera

Cited by 26 publications

References 39 publications

A Review of the Environmental Trigger and Transmission Components for Prediction of Cholera

A Review of the Environmental Trigger and Transmission Components for Prediction of Cholera

A dynamic optimal control model for COVID-19 and cholera co-infection in Yemen

A general multipatch cholera model in periodic environments

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