Water, Sanitation, and Cholera in Sub-Saharan Africa.

Improvements in water and sanitation should reduce cholera risk though the associations between cholera and specific water and sanitation access measures remain unclear. We estimated the association between eight water and sanitation measures and annual cholera incidence access across sub-Saharan Africa (2010-2016) for data aggregated at the country and district levels. We fit random forest regression and classification models to understand how well these measures combined might be able to predict cholera incidence rates and identify high cholera incidence areas. Across spatial scales, piped or "other improved" water access was inversely associated with cholera incidence. Access to piped water, septic or sewer sanitation, and septic, sewer, or "other improved" sanitation were associated with decreased district-level cholera incidence. The classification model had moderate performance in identifying high cholera incidence areas (cross-validated-AUC 0.81, 95% CI 0.78-0.83) with high negative predictive values (93-100%) indicating the utility of water and sanitation measures for screening out areas that are unlikely to be at high cholera risk. While comprehensive cholera risk assessments must incorporate other data sources (e.g., historical incidence), our results suggest that water and sanitation measures could alone be useful in narrowing the geographic focus for detailed risk assessments.

Prioritizing interventions for cholera control in Kenya, 2015-2020.

Kenya has experienced cholera outbreaks since 1971, with the most recent wave beginning in late 2014. Between 2015-2020, 32 of 47 counties reported 30,431 suspected cholera cases. The Global Task Force for Cholera Control (GTFCC) developed a Global Roadmap for Ending Cholera by 2030, which emphasizes the need to target multi-sectoral interventions in priority cholera burden hotspots. This study utilizes the GTFCC's hotspot method to identify hotspots in Kenya at the county and sub-county administrative levels from 2015 through 2020. 32 of 47 (68.1%) counties reported cholera cases during this time while only 149 of 301 (49.5%) sub-counties reported cholera cases. The analysis identifies hotspots based on the mean annual incidence (MAI) over the past five-year period and cholera's persistence in the area. Applying a MAI threshold of 90th percentile and the median persistence at both the county and sub-county levels, we identified 13 high risk sub-counties from 8 counties, including the 3 high risk counties of Garissa, Tana River and Wajir. This demonstrates that several sub-counties are high level hotspots while their counties are not. In addition, when cases reported by county versus sub-county hotspot risk are compared, 1.4 million people overlapped in the areas identified as both high-risk county and high-risk sub-county. However, assuming that finer scale data is more accurate, 1.6 million high risk sub-county people would have been misclassified as medium risk with a county-level analysis. Furthermore, an additional 1.6 million people would have been classified as living in high-risk in a county-level analysis when at the sub-county level, they were medium, low or no-risk sub-counties. This results in 3.2 million people being misclassified when county level analysis is utilized rather than a more-focused sub-county level analysis. This analysis highlights the need for more localized risk analyses to target cholera intervention and prevention efforts towards the populations most vulnerable.

HIT-COVID, a global database tracking public health interventions to COVID-19.

The COVID-19 pandemic has sparked unprecedented public health and social measures (PHSM) by national and local governments, including border restrictions, school closures, mandatory facemask use and stay at home orders. Quantifying the effectiveness of these interventions in reducing disease transmission is key to rational policy making in response to the current and future pandemics. In order to estimate the effectiveness of these interventions, detailed descriptions of their timelines, scale and scope are needed. The Health Intervention Tracking for COVID-19 (HIT-COVID) is a curated and standardized global database that catalogues the implementation and relaxation of COVID-19 related PHSM. With a team of over 200 volunteer contributors, we assembled policy timelines for a range of key PHSM aimed at reducing COVID-19 risk for the national and first administrative levels (e.g. provinces and states) globally, including details such as the degree of implementation and targeted populations. We continue to maintain and adapt this database to the changing COVID-19 landscape so it can serve as a resource for researchers and policymakers alike.