Spatial dynamics and the basic reproduction number of the 1991-1997 Cholera epidemic in Peru

Satellite-Derived, Smartphone-Delivered Geospatial Cholera Risk Information for Vulnerable Populations

Cholera, an acute waterborne diarrheal disease, remains a major global health challenge. Despite being curable and preventable, it can be fatal if left untreated, especially for children. Bangladesh, a cholera-endemic country with a high disease burden, experiences two peaks annually, during the dry pre-monsoon spring and the wet post-monsoon fall seasons. An early warning system for disseminating cholera risk, which has potential to reduce the disease burden, currently does not exist in Bangladesh. Such systems can raise timely awareness and allow households in rural, riverine areas like Matlab to make behavioral adjustments with water usage and around water resources to reduce contracting and transmitting cholera. Current dissemination approaches typically target local government and public health organizations; however, the vulnerable rural populations largely remain outside the information chain. Here, we develop and evaluate the accuracy of an early warning system-CholeraMap that uses high-resolution earth observations to forecast cholera risk and disseminate geocoded risk maps directly to Matlab's population via a mobile smartphone application. Instead of relying on difficult to obtain station-based environmental and hydroclimatological data, this study offers a new opportunity to use remote sensing data sets for designing and operating a disease early warning system. CholeraMap delivers monthly, color-coded geospatial maps (1 km × 1 km spatial resolution) with household and community cholera risk information. Our results demonstrate that the satellite-derived local-scale risk model satisfactorily captured the seasonal cholera pattern for the Matlab region, and a detailed high-resolution picture of the spatial progression of at-risk areas during outbreak months.

Clinical surveillance systems obscure the true cholera infection burden in an endemic region

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.

Reconstruction of incidence reporting rate for SARS-CoV-2 Delta variant of COVID-19 pandemic in the US

In recent years, advanced regularization techniques have emerged as a powerful tool aimed at stable estimation of infectious disease parameters that are crucial for future projections, prevention, and control. Unlike other system parameters, i.e., incubation and recovery rates, the case reporting rate, Ψ, and the time-dependent effective reproduction number, R e ( t ) , are directly influenced by a large number of factors making it impossible to pre-estimate these parameters in any meaningful way. In this study, we propose a novel iteratively-regularized trust-region optimization algorithm, combined with SuSvIuIvRD compartmental model, for stable reconstruction of Ψ and R e ( t ) from reported epidemic data on vaccination percentages, incidence cases, and daily deaths. The innovative regularization procedure exploits (and takes full advantage of) a unique structure of the Jacobian and Hessian approximation for the nonlinear observation operator. The proposed inversion method is thoroughly tested with synthetic and real SARS-CoV-2 Delta variant data for different regions in the United States of America from July 9, 2021, to November 25, 2021. Our study shows that case reporting rate during the Delta wave of COVID-19 pandemic in the US is between 12% and 37%, with most states being in the range from 15% to 25%. This confirms earlier accounts on considerable under-reporting of COVID-19 cases due to the impact of "silent spreaders" and the limitations of testing.

Estimating the gap between clinical cholera and true community infections: findings from an integrated surveillance study in an endemic region of Bangladesh

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.

Spatio-temporal small area surveillance of the COVID-19 pandemic

The emergence of COVID-19 requires new effective tools for epidemiological surveillance. Spatio-temporal disease mapping models, which allow dealing with small units of analysis, are a priority in this context. These models provide geographically detailed and temporally updated overviews of the current state of the pandemic, making public health interventions more effective. These models also allow estimating epidemiological indicators highly demanded for COVID-19 surveillance, such as the instantaneous reproduction number R t , even for small areas. In this paper, we propose a new spatio-temporal spline model particularly suited for COVID-19 surveillance, which allows estimating and monitoring R t for small areas. We illustrate our proposal on the study of the disease pandemic in two Spanish regions. As a result, we show how tourism flows have shaped the spatial distribution of the disease in these regions. In these case studies, we also develop new epidemiological tools to be used by regional public health services for small area surveillance.

Living at High Altitude and COVID-19 Mortality in Peru

Nicolaou, Laura, Anne Steinberg, Rodrigo M. Carrillo-Larco, Stella Hartinger, Andres G. Lescano, and William Checkley. Living at high altitude and COVID-19 mortality in Peru. High Alt Med Biol. 23:146-158, 2022. Background: Previous studies have reported a lower severity of COVID-19 infections at higher altitudes; however, this association may be confounded by various factors. We examined the association between living at altitude and COVID-19 mortality in Peru adjusting for population density, prevalence of comorbidities, indicators of socioeconomic status, and health care access. Methods: Utilizing administrative data across 196 provinces located at varying altitudes (sea level to 4,373 m), we conducted a two-stage analysis of COVID-19 deaths between March 19 and December 31, 2020, Peru's first wave. We first calculated cumulative daily mortality rate for each province and fit lognormal cumulative distribution functions to estimate total mortality rate, and start, peak, and duration of the first wave. We then regressed province-level total mortality rate, start, peak, and duration of the first wave as a function of altitude adjusted for confounders. Results: There were 93,528 recorded deaths from COVID-19 (mean age 66.5 years, 64.5% male) for a cumulative mortality of 272.5 per 100,000 population between March 19 and December 31, 2020. We did not find a consistent monotonic trend between living at higher altitudes and estimated total mortality rate for provinces at 500 - 1,000 m (-12.1 deaths per 100,000 population per 100 m, 95% familywise confidence interval -27.7 to 3.5) or > 1,000 m (-0.3, -2.7 to 2.0). We also did not find consistent monotonic trends for the start, peak, and duration of the first wave beyond the first 500 m. Conclusions: Our findings suggest that living at high altitude may not confer a lower risk of death from COVID-19.

Cholera

Cholera was first described in the areas around the Bay of Bengal and spread globally, resulting in seven pandemics during the past two centuries. It is caused by toxigenic Vibrio cholerae O1 or O139 bacteria. Cholera is characterised by mild to potentially fatal acute watery diarrhoeal disease. Prompt rehydration therapy is the cornerstone of management. We present an overview of cholera and its pathogenesis, natural history, bacteriology, and epidemiology, while highlighting advances over the past 10 years in molecular epidemiology, immunology, and vaccine development and deployment. Since 2014, the Global Task Force on Cholera Control, a WHO coordinated network of partners, has been working with several countries to develop national cholera control strategies. The global roadmap for cholera control focuses on stopping transmission in cholera hotspots through vaccination and improved water, sanitation, and hygiene, with the aim to reduce cholera deaths by 90% and eliminate local transmission in at least 20 countries by 2030.

Cholera dynamics: lessons from an epidemic

Cholera is a severe diarrhoeal disease that spreads rapidly and affects millions of people each year, resulting in tens of thousands of deaths. The disease is caused by Vibrio cholerae O1 and is characterized by watery diarrhoea that can be lethal if not properly treated. Cholera had not been reported in South America from the late 1800s until 1991, when it was introduced in Peru, wreaking havoc in one of the biggest epidemics reported to date. Within a year, the disease had spread to most of the Latin American region, resulting in millions of cases and thousands of deaths in all affected countries. Despite its aggressive entry, cholera virtually disappeared from the continent after 1999. The progression of the entire epidemic was well documented, making it an ideal model to understand cholera dynamics. In this review, we highlight how the synergy of socioeconomic, political and ecological factors led to the emergence, rapid spread and eventual disappearance of cholera in Latin America. We discuss how measures implemented during the cholera epidemic drastically changed its course and continental dynamics. Finally, we synthesize our findings and highlight potential lessons that can be learned for efficient and standardized cholera management programmes during future outbreaks in non-endemic areas.