Epidemic cholera spreads like wildfire

The costs and benefits of primary prevention of zoonotic pandemics

The lives lost and economic costs of viral zoonotic pandemics have steadily increased over the past century. Prominent policymakers have promoted plans that argue the best ways to address future pandemic catastrophes should entail, "detecting and containing emerging zoonotic threats." In other words, we should take actions only after humans get sick. We sharply disagree. Humans have extensive contact with wildlife known to harbor vast numbers of viruses, many of which have not yet spilled into humans. We compute the annualized damages from emerging viral zoonoses. We explore three practical actions to minimize the impact of future pandemics: better surveillance of pathogen spillover and development of global databases of virus genomics and serology, better management of wildlife trade, and substantial reduction of deforestation. We find that these primary pandemic prevention actions cost less than 1/20th the value of lives lost each year to emerging viral zoonoses and have substantial cobenefits.

Intensity and frequency of extreme novel epidemics

Observational knowledge of the epidemic intensity, defined as the number of deaths divided by global population and epidemic duration, and of the rate of emergence of infectious disease outbreaks is necessary to test theory and models and to inform public health risk assessment by quantifying the probability of extreme pandemics such as COVID-19. Despite its significance, assembling and analyzing a comprehensive global historical record spanning a variety of diseases remains an unexplored task. A global dataset of historical epidemics from 1600 to present is here compiled and examined using novel statistical methods to estimate the yearly probability of occurrence of extreme epidemics. Historical observations covering four orders of magnitude of epidemic intensity follow a common probability distribution with a slowly decaying power-law tail (generalized Pareto distribution, asymptotic exponent = -0.71). The yearly number of epidemics varies ninefold and shows systematic trends. Yearly occurrence probabilities of extreme epidemics, P_y, vary widely: P_y of an event with the intensity of the "Spanish influenza" (1918 to 1920) varies between 0.27 and 1.9% from 1600 to present, while its mean recurrence time today is 400 y (95% CI: 332 to 489 y). The slow decay of probability with epidemic intensity implies that extreme epidemics are relatively likely, a property previously undetected due to short observational records and stationary analysis methods. Using recent estimates of the rate of increase in disease emergence from zoonotic reservoirs associated with environmental change, we estimate that the yearly probability of occurrence of extreme epidemics can increase up to threefold in the coming decades.

Information differences across spatial resolutions and scales for disease surveillance and analysis: The case of Visceral Leishmaniasis in Brazil

Nationwide disease surveillance at a high spatial resolution is desired for many infectious diseases, including Visceral Leishmaniasis. Statistical and mathematical models using data collected from surveillance activities often use a spatial resolution and scale either constrained by data availability or chosen arbitrarily. Sensitivity of model results to the choice of spatial resolution and scale is not, however, frequently evaluated. This study aims to determine if the choice of spatial resolution and scale are likely to impact statistical and mathematical analyses. Visceral Leishmaniasis in Brazil is used as a case study. Probabilistic characteristics of disease incidence, representing a likely outcome in a model, are compared across spatial resolutions and scales. Best fitting distributions were fit to annual incidence from 2004 to 2014 by municipality and by state. Best fits were defined as the distribution family and parameterization minimizing the sum of absolute error, evaluated through a simulated annealing algorithm. Gamma and Poisson distributions provided best fits for incidence, both among individual states and nationwide. Comparisons of distributions using Kullback-Leibler divergence shows that incidence by state and by municipality do not follow distributions that provide equivalent information. Few states with Gamma distributed incidence follow a distribution closely resembling that for national incidence. These results demonstrate empirically how choice of spatial resolution and scale can impact mathematical and statistical models.

The case-area targeted rapid response strategy to control cholera in Haiti: a four-year implementation study

BACKGROUND

In October 2010, Haiti was struck by a large-scale cholera epidemic. The Haitian government, UNICEF and other international partners launched an unprecedented nationwide alert-response strategy in July 2013. Coordinated NGOs recruited local rapid response mobile teams to conduct case-area targeted interventions (CATIs), including education sessions, household decontamination by chlorine spraying, and distribution of chlorine tablets. An innovative red-orange-green alert system was also established to monitor the epidemic at the communal scale on a weekly basis. Our study aimed to describe and evaluate the exhaustiveness, intensity and quality of the CATIs in response to cholera alerts in Haiti between July 2013 and June 2017.

METHODOLOGY/PRINCIPAL FINDINGS

We analyzed the response to 7,856 weekly cholera alerts using routine surveillance data and severity criteria, which was based on the details of 31,306 notified CATIs. The odds of CATI response during the same week (exhaustiveness) and the number of complete CATIs in responded alerts (intensity and quality) were estimated using multivariate generalized linear mixed models and several covariates. CATIs were carried out significantly more often in response to red alerts (adjusted odds ratio (aOR) [95%-confidence interval, 95%-CI], 2.52 [2.22-2.87]) compared with orange alerts. Significantly more complete CATIs were carried out in response to red alerts compared with orange alerts (adjusted incidence ratio (aIR), 1.85 [1.73-1.99]). Over the course of the eight-semester study, we observed a significant improvement in the exhaustiveness (aOR, 1.43 [1.38-1.48] per semester) as well as the intensity and quality (aIR, 1.23 [1.2-1.25] per semester) of CATI responses, independently of funds available for the strategy. The odds of launching a CATI response significantly decreased with increased rainfall (aOR, 0.99 [0.97-1] per each accumulated cm). Response interventions were significantly heterogeneous between NGOs, communes and departments.

CONCLUSIONS/SIGNIFICANCE

The implementation of a nationwide case-area targeted rapid response strategy to control cholera in Haiti was feasible albeit with certain obstacles. Such feedback from the field and ongoing impact studies will be very informative for actors and international donors involved in cholera control and elimination in Haiti and in other affected countries.

Human evolutionary loss of epithelial Neu5Gc expression and species-specific susceptibility to cholera

While infectious agents have typical host preferences, the noninvasive enteric bacterium Vibrio cholerae is remarkable for its ability to survive in many environments, yet cause diarrheal disease (cholera) only in humans. One key V. cholerae virulence factor is its neuraminidase (VcN), which releases host intestinal epithelial sialic acids as a nutrition source and simultaneously remodels intestinal polysialylated gangliosides into monosialoganglioside GM1. GM1 is the optimal binding target for the B subunit of a second virulence factor, the AB5 cholera toxin (Ctx). This coordinated process delivers the CtxA subunit into host epithelia, triggering fluid loss via cAMP-mediated activation of anion secretion and inhibition of electroneutral NaCl absorption. We hypothesized that human-specific and human-universal evolutionary loss of the sialic acid N-glycolylneuraminic acid (Neu5Gc) and the consequent excess of N-acetylneuraminic acid (Neu5Ac) contributes to specificity at one or more steps in pathogenesis. Indeed, VcN was less efficient in releasing Neu5Gc than Neu5Ac. We show enhanced binding of Ctx to sections of small intestine and isolated polysialogangliosides from human-like Neu5Gc-deficient Cmah-/- mice compared to wild-type, suggesting that Neu5Gc impeded generation of the GM1 target. Human epithelial cells artificially expressing Neu5Gc were also less susceptible to Ctx binding and CtxA intoxication following VcN treatment. Finally, we found increased fluid secretion into loops of Cmah-/- mouse small intestine injected with Ctx, indicating an additional direct effect on ion transport. Thus, V. cholerae evolved into a human-specific pathogen partly by adapting to the human evolutionary loss of Neu5Gc, optimizing multiple steps in cholera pathogenesis.

Cholera outbreak in a naïve rural community in Northern Nigeria: the importance of hand washing with soap, September 2010

INTRODUCTION

Cholera outbreaks in rural communities are associated with high morbidity and mortality. Effective interventions to control these outbreaks require identification of source and risk factors for infection. In September, 2010 we investigated a cholera outbreak in Bashuri, a cholera naïve rural community in northern Nigeria to identify the risk factors and institute control measures.

METHODS

We conducted an unmatched case-control study. We defined a case as any resident of Bashuri community two years and above with acute watery diarrhea with or without vomiting and a control as any resident two years and above without acute watery diarrhea and vomiting. We recruited 80 hospital-based cases and 80 neighborhood controls. We collected and analyzed data on demographic characteristics, clinical information and risk factors. Laboratory analysis was performed on 10 stool samples and 14 open-well samples.

RESULTS

Mean age was 29 years (± 20 years) for cases and 32 years (± 16 years) for controls; 38 (47.5%) of cases and 60 (75%) of controls were males. Compared to controls, cases were less likely to have washed hands with soap before eating (age-adjusted odds ratio (AAOR) = 0.27, 95% confidence interval (CI): 0.10-0.72) and less likely to have washed hands with soap after using the toilet (AAOR = 0.34, 95% CI: 0.15-0.75). Vibrio cholerae O1 was isolated from six stool samples but not from any open-well samples.

CONCLUSION

Unhygienic hand washing practices was the key risk factor in this outbreak. We educated the community on personal hygiene focusing on the importance of hand washing with soap.

Integrated view of Vibrio cholerae in the Americas

Latin America has experienced two of the largest cholera epidemics in modern history; one in 1991 and the other in 2010. However, confusion still surrounds the relationships between globally circulating pandemic Vibrio cholerae clones and local bacterial populations. We used whole-genome sequencing to characterize cholera across the Americas over a 40-year time span. We found that both epidemics were the result of intercontinental introductions of seventh pandemic El Tor V. cholerae and that at least seven lineages local to the Americas are associated with disease that differs epidemiologically from epidemic cholera. Our results consolidate historical accounts of pandemic cholera with data to show the importance of local lineages, presenting an integrated view of cholera that is important to the design of future disease control strategies.

Forecasting Epidemiological and Evolutionary Dynamics of Infectious Diseases

Mathematical models have been powerful tools in developing mechanistic understanding of infectious diseases. Furthermore, they have allowed detailed forecasting of epidemiological phenomena such as outbreak size, which is of considerable public-health relevance. The short generation time of pathogens and the strong selection they are subjected to (by host immunity, vaccines, chemotherapy, etc.) mean that evolution is also a key driver of infectious disease dynamics. Accurate forecasting of pathogen dynamics therefore calls for the integration of epidemiological and evolutionary processes, yet this integration remains relatively rare. We review previous attempts to model and predict infectious disease dynamics with or without evolution and discuss major challenges facing the development of the emerging science of epidemic forecasting.

A Theoretical Analysis of the Geography of Schistosomiasis in Burkina Faso Highlights the Roles of Human Mobility and Water Resources Development in Disease Transmission

We study the geography of schistosomiasis across Burkina Faso by means of a spatially explicit model of water-based disease dynamics. The model quantitatively addresses the geographic stratification of disease burden in a novel framework by explicitly accounting for drivers and controls of the disease, including spatial information on the distributions of population and infrastructure, jointly with a general description of human mobility and climatic/ecological drivers. Spatial patterns of disease are analysed by the extraction and the mapping of suitable eigenvectors of the Jacobian matrix subsuming the stability of the disease-free equilibrium. The relevance of the work lies in the novel mapping of disease burden, a byproduct of the parametrization induced by regional upscaling, by model-guided field validations and in the predictive scenarios allowed by exploiting the range of possible parameters and processes. Human mobility is found to be a primary control at regional scales both for pathogen invasion success and the overall distribution of disease burden. The effects of water resources development highlighted by systematic reviews are accounted for by the average distances of human settlements from water bodies that are habitats for the parasite's intermediate host. Our results confirm the empirical findings about the role of water resources development on disease spread into regions previously nearly disease-free also by inspection of empirical prevalence patterns. We conclude that while the model still needs refinements based on field and epidemiological evidence, the proposed framework provides a powerful tool for large-scale public health planning and schistosomiasis management.

Modeling the Impact of White-Plague Coral Disease in Climate Change Scenarios

Coral reefs are in global decline, with coral diseases increasing both in prevalence and in space, a situation that is expected only to worsen as future thermal stressors increase. Through intense surveillance, we have collected a unique and highly resolved dataset from the coral reef of Eilat (Israel, Red Sea), that documents the spatiotemporal dynamics of a White Plague Disease (WPD) outbreak over the course of a full season. Based on modern statistical methodologies, we develop a novel spatial epidemiological model that uses a maximum-likelihood procedure to fit the data and assess the transmission pattern of WPD. We link the model to sea surface temperature (SST) and test the possible effect of increasing temperatures on disease dynamics. Our results reveal that the likelihood of a susceptible coral to become infected is governed both by SST and by its spatial location relative to nearby infected corals. The model shows that the magnitude of WPD epidemics strongly depends on demographic circumstances; under one extreme, when recruitment is free-space regulated and coral density remains relatively constant, even an increase of only 0.5°C in SST can cause epidemics to double in magnitude. In reality, however, the spatial nature of transmission can effectively protect the community, restricting the magnitude of annual epidemics. This is because the probability of susceptible corals to become infected is negatively associated with coral density. Based on our findings, we expect that infectious diseases having a significant spatial component, such as Red-Sea WPD, will never lead to a complete destruction of the coral community under increased thermal stress. However, this also implies that signs of recovery of local coral communities may be misleading; indicative more of spatial dynamics than true rehabilitation of these communities. In contrast to earlier generic models, our approach captures dynamics of WPD both in space and time, accounting for the highly seasonal nature of annual WPD outbreaks.

Coral reefs are deteriorating at alarming rates, with coral disease outbreaks increasing in prevalence and in space. Anomalously high ocean temperatures are thought to significantly contribute to this problem. We collected a unique and highly resolved dataset of a White Plague Disease (WPD) outbreak from the coral reef of Eilat (Israel, Red Sea). By fitting a novel epidemiological model to the data, we characterize the dynamics of WPD, and study the possible effects of future increasing sea-surface temperatures (SST) on disease dynamics. In contrast to earlier studies, our approach captures the dynamics of coral disease both in space and time, and accounts for the highly seasonal nature of the annual outbreaks. We also apply a novel combination of spatiotemporal statistics and null hypothesis approaches to study the disease progression. Model forecasts into the future show that for some scenarios even an increase of only 0.5°C in SST can cause epidemics to double in magnitude. Since the probability of infection is found to be negatively associated with coral density, this implies that the spatial nature of disease transmission can both enhance and restrict the magnitude of annual epidemics. The results have implications for designing management policies appropriate for coral reef conservation.