Publications by authors named "Samuel Canfield"
Increasingly, geographic approaches to assessing the risk of tick-borne diseases are being used to inform public health decision-making and surveillance efforts. The distributions of key tick species of medical importance are often modeled as a function of environmental factors, using niche modeling approaches to capture habitat suitability. However, this is often disconnected from the potential distribution of key host species, which may play an important role in the actual transmission cycle and risk potential in expanding tick-borne disease risk.
View Article and Find Full Text PDFUsing data collected from previous (n = 86) and prospective (n = 132) anthrax outbreaks, we enhanced prior ecological niche models (ENM) and added kernel density estimation (KDE) approaches to identify anthrax hotspots in Kenya. Local indicators of spatial autocorrelation (LISA) identified clusters of administrative wards with a relatively high or low anthrax reporting rate to determine areas of greatest outbreak intensity. Subsequently, we modeled the impact of vaccinating livestock in the identified hotspots as a national control measure.
View Article and Find Full Text PDFArticle Synopsis
- Climate change is expected to increase the prevalence and geographical spread of infectious diseases like anthrax, particularly in regions like Kenya where knowledge about these impacts is limited.
- The study used ecological niche modeling with historical anthrax occurrence data to predict future distributions of the disease under different climate scenarios for the year 2055.
- Findings show a predicted expansion of anthrax risk areas from 36,131 km² currently to approximately 40,012 km² and 39,835 km² under climate change scenarios RCP 4.5 and 8.5, respectively, with a notable northward shift in distribution.
Article Synopsis
- - Anthrax in Kenya poses significant health and economic challenges, often occurring in outbreaks involving animals and humans, with limited understanding of geographic distribution factors affecting these outbreaks.
- - A boosted regression trees (BRT) analysis was conducted on anthrax surveillance data from 2011 to 2017, revealing key environmental factors such as cattle density and rainfall that influence anthrax suitability across the region.
- - The study identified high-suitability areas for anthrax mainly in southwestern Kenya and central highlands, providing valuable information for policymakers to enhance surveillance and control strategies in agriculture and wildlife sectors.