A transmission model of the 2010 cholera epidemic in Haiti

Transmission dynamics of cholera in Yemen, 2017: a real time forecasting

BACKGROUND

A large epidemic of cholera, caused by Vibrio cholerae, serotype Ogawa, has been ongoing in Yemen, 2017. To improve the situation awareness, the present study aimed to forecast the cholera epidemic, explicitly addressing the reporting delay and ascertainment bias.

METHODS

Using weekly incidence of suspected cases, updated as a revised epidemic curve every week, the reporting delay was explicitly incorporated into the estimation model. Using the weekly case fatality risk as calculated by the World Health Organization, ascertainment bias was adjusted, enabling us to parameterize the family of logistic curves (i.e., logistic and generalized logistic models) for describing the unbiased incidence in 2017.

RESULTS

The cumulative incidence at the end of the epidemic, was estimated at 790,778 (95% CI: 700,495, 914,442) cases and 767,029 (95% CI: 690,877, 871,671) cases, respectively, by using logistic and generalized logistic models. It was also estimated that we have just passed through the epidemic peak by week 26, 2017. From week 27 onwards, the weekly incidence was predicted to decrease.

CONCLUSIONS

Cholera epidemic in Yemen, 2017 was predicted to soon start to decrease. If the weekly incidence is reported in the up-to-the-minute manner and updated in later weeks, not a single data point but the entire epidemic curve must be precisely updated.

Cholera transmission dynamic models for public health practitioners

Great progress has been made in mathematical models of cholera transmission dynamics in recent years. However, little impact, if any, has been made by models upon public health decision-making and day-to-day routine of epidemiologists. This paper provides a brief introduction to the basics of ordinary differential equation models of cholera transmission dynamics. We discuss a basic model adapted from Codeço (2001), and how it can be modified to incorporate different hypotheses, including the importance of asymptomatic or inapparent infections, and hyperinfectious V. cholerae and human-to-human transmission. We highlight three important challenges of cholera models: (1) model misspecification and parameter uncertainty, (2) modeling the impact of water, sanitation and hygiene interventions and (3) model structure. We use published models, especially those related to the 2010 Haitian outbreak as examples. We emphasize that the choice of models should be dictated by the research questions in mind. More collaboration is needed between policy-makers, epidemiologists and modelers in public health.

Complexity in mathematical models of public health policies: a guide for consumers of models

Sanjay Basu and colleagues explain how models are increasingly used to inform public health policy yet readers may struggle to evaluate the quality of models. All models require simplifying assumptions, and there are tradeoffs between creating models that are more "realistic" versus those that are grounded in more solid data. Indeed, complex models are not necessarily more accurate or reliable simply because they can more easily fit real-world data than simpler models can. Please see later in the article for the Editors' Summary.

The regulatory network of natural competence and transformation of Vibrio cholerae

The human pathogen Vibrio cholerae is an aquatic bacterium frequently encountered in rivers, lakes, estuaries, and coastal regions. Within these environmental reservoirs, the bacterium is often found associated with zooplankton and more specifically with their chitinous exoskeleton. Upon growth on such chitinous surfaces, V. cholerae initiates a developmental program termed “natural competence for genetic transformation.” Natural competence for transformation is a mode of horizontal gene transfer in bacteria and contributes to the maintenance and evolution of bacterial genomes. In this study, we investigated competence gene expression within this organism at the single cell level. We provide evidence that under homogeneous inducing conditions the majority of the cells express competence genes. A more heterogeneous expression pattern was observable on chitin surfaces. We hypothesize that this was the case due to the heterogeneity around the chitin surface, which might vary extensively with respect to chitin degradation products and autoinducers; these molecules contribute to competence induction based on carbon catabolite repression and quorum-sensing pathways, respectively. Therefore, we investigated the contribution of these two signaling pathways to natural competence in detail using natural transformation assays, transcriptional reporter fusions, quantitative RT–PCR, and immunological detection of protein levels using Western blot analysis. The results illustrate that all tested competence genes are dependent on the transformation regulator TfoX. Furthermore, intracellular cAMP levels play a major role in natural transformation. Finally, we demonstrate that only a minority of genes involved in natural transformation are regulated in a quorum-sensing-dependent manner and that these genes determine the fate of the surrounding DNA. We conclude with a model of the regulatory circuit of chitin-induced natural competence in V. cholerae.

The human pathogen Vibrio cholerae is an aquatic bacterium often encountered in rivers, estuaries, and coastal regions. Within this environmental niche, the bacterium often associates with the chitinous exoskeleton of zooplankton. Upon colonization of these chitinous surfaces, V. cholerae switches on a developmental program known as natural competence for genetic transformation. Natural competence for transformation is a mode of horizontal gene transfer that allows bacteria to acquire new genes derived from free DNA, which is released by other members within the same habitat. The evolutionary consequences could be that the bacterial recipient becomes better adapted to its environmental niche or, in a worst-case scenario, more pathogenic for man. The results of this study show that, under optimal conditions, the majority of cells within a V. cholerae population express competence genes. However, in an aquatic environment, a combination of different ecological factors might lead to heterogeneity in the competence phenotype. Therefore, we investigated the role of extracellular and intracellular signaling molecules with respect to competence induction. This report illustrates that at least three interconnected signaling cascades are required for competence induction, which are based on bacterial metabolism and group behavior.

Reassessment of the 2010-2011 Haiti cholera outbreak and rainfall-driven multiseason projections

Mathematical models can provide key insights into the course of an ongoing epidemic, potentially aiding real-time emergency management in allocating health care resources and by anticipating the impact of alternative interventions. We study the ex post reliability of predictions of the 2010-2011 Haiti cholera outbreak from four independent modeling studies that appeared almost simultaneously during the unfolding epidemic. We consider the impact of different approaches to the modeling of spatial spread of Vibrio cholerae and mechanisms of cholera transmission, accounting for the dynamics of susceptible and infected individuals within different local human communities. To explain resurgences of the epidemic, we go on to include waning immunity and a mechanism explicitly accounting for rainfall as a driver of enhanced disease transmission. The formal comparative analysis is carried out via the Akaike information criterion (AIC) to measure the added information provided by each process modeled, discounting for the added parameters. A generalized model for Haitian epidemic cholera and the related uncertainty is thus proposed and applied to the year-long dataset of reported cases now available. The model allows us to draw predictions on longer-term epidemic cholera in Haiti from multiseason Monte Carlo runs, carried out up to January 2014 by using suitable rainfall fields forecasts. Lessons learned and open issues are discussed and placed in perspective. We conclude that, despite differences in methods that can be tested through model-guided field validation, mathematical modeling of large-scale outbreaks emerges as an essential component of future cholera epidemic control.