Predictive Intelligence for Cholera in Ukraine?

Assessment of water scarcity as a risk factor for cholera outbreaks

INTRODUCTION

Increasing aridity and incidence of droughts pose a significant threat to human health, primarily in exacerbating water scarcity, and is projected to become more frequent and severe as a result of related environmental changes in many regions globally. Concomitantly, water scarcity will force populations to utilize potentially contaminated water sources, hence increasing exposure to waterborne diseases, notably cholera. Proliferation of Vibrio cholerae, causative agent of cholera, is driven by environmental factors. Notably, temperature and precipitation have been employed in providing predictive awareness of cholera, allowing early warning and mitigation. The impact of droughts on incidence and spread of cholera is less understood.

METHODS

This study aimed to quantify relationships among temperature, precipitation, and droughts as a basis for establishing the connection of environmental parameters and outbreaks of cholera. Thirteen cholera outbreaks between 2003 and 2023 in four African countries (Ethiopia, Kenya, Nigeria, and Senegal) were assessed using odds ratio and k-means clustering analysis.

RESULTS

Cholera outbreaks were 3.07 (95 % CI: [0.95, 9.88]) times more likely when drought conditions (negative precipitation anomalies, positive temperature anomalies, and negative Standardized Precipitation-Evapotranspiration Index) were present, compared to their absence. When excess rainfall was also considered, the odds ratio increased to 3.50 (95 % CI: [1.03, 11.90]). Complementary evidence obtained using k-means clustering analysis supported the conclusion that outbreaks of cholera were common during drought conditions.

CONCLUSIONS

Considering the last few decades with increased severity and frequency of droughts in cholera-impacted regions, climate projections indicate the threat of cholera outbreaks will continue, especially noting increasing reports of cholera globally. Hence, predictive intelligence systems for rapid risk assessment, with respect to climate, drought, and human health, are warranted.

Quantification of Climate Footprints of Vibrio vulnificus in Coastal Human Communities of the United States Gulf Coast

The incidence of vibriosis is rising globally with evidence of climate variability influencing environmental processes that support growth of pathogenic Vibrio spp. The waterborne pathogen, Vibrio vulnificus can invade wounds and has one of the highest case fatality rates in humans. The bacterium cannot be eradicated from the aquatic environment, hence climate driven environmental conditions enhancing growth and dissemination of V. vulnificus need to be understood to provide preemptive assessment of its presence and distribution in aquatic systems. To achieve this objective, satellite remote sensing was employed to quantify the association of sea surface temperature (SST) and chlorophyll-a (chl-a) in locations with reported V. vulnificus infections. Monthly analysis was done in two populated regions of the Gulf of Mexico-Tampa Bay, Florida, and Galveston Bay, Texas. Results indicate warm water, characterized by a 2-month lag in SST, high concentration of phytoplankton, proxied for zooplankton using 1 month lagged chl-a values, was statistically linked to higher odds of V. vulnificus infection in the human population. Identification of climate and ecological processes thresholds is concluded to be useful for development of an heuristic prediction system designed to determine risk of infection for coastal populations.

Genomic diversity of Vibrio spp. and metagenomic analysis of pathogens in Florida Gulf coastal waters following Hurricane Ian

IMPORTANCE

Evidence suggests warming temperatures are associated with the spread of potentially pathogenic Vibrio spp. and the emergence of human disease globally. Following Hurricane Ian, the State of Florida reported a sharp increase in the number of reported Vibrio spp. infections and deaths. Hence, monitoring of pathogens, including vibrios, and environmental parameters influencing their occurrence is critical to public health. Here, DNA sequencing was used to investigate the genomic diversity of Vibrio parahaemolyticus and Vibrio vulnificus, both potential human pathogens, in Florida coastal waters post Hurricane Ian, in October 2022. Additionally, the microbial community of water samples was profiled to detect the presence of Vibrio spp. and other microorganisms (bacteria, fungi, protists, and viruses) present in the samples. Long-term environmental data analysis showed changes in environmental parameters during and after Ian were optimal for the growth of Vibrio spp. and related pathogens. Collectively, results will be used to develop predictive risk models during climate change.

Anticipatory decision-making for cholera in Malawi

Climate change raises an old disease to a new level of public health threat. The causative agent, Vibrio cholerae, native to aquatic ecosystems, is influenced by climate and weather processes. The risk of cholera is elevated in vulnerable populations lacking access to safe water and sanitation infrastructure. Predictive intelligence, employing mathematical algorithms that integrate earth observations and heuristics derived from microbiological, sociological, and weather data, can provide anticipatory decision-making capabilities to reduce the burden of cholera and save human lives. An example offered here is the recent outbreak of cholera in Malawi, predicted in advance by such algorithms.

Combating cholera by building predictive capabilities for pathogenic Vibrio cholerae in Yemen

Cholera remains a global public health threat in regions where social vulnerabilities intersect with climate and weather processes that impact infectious Vibrio cholerae. While access to safe drinking water and sanitation facilities limit cholera outbreaks, sheer cost of building such infrastructure limits the ability to safeguard the population. Here, using Yemen as an example where cholera outbreak was reported in 2016, we show how predictive abilities for forecasting risk, employing sociodemographical, microbiological, and climate information of cholera, can aid in combating disease outbreak. An epidemiological analysis using Bradford Hill Criteria was employed in near-real-time to understand a predictive model's outputs and cholera cases in Yemen. We note that the model predicted cholera risk at least four weeks in advance for all governorates of Yemen with overall 72% accuracy (varies with the year). We argue the development of anticipatory decision-making frameworks for climate modulated diseases to design intervention activities and limit exposure of pathogens preemptively.