One Health Longitudinal Study Protocol on Zoonotic and Vector-Borne Diseases in Battambang province, Cambodia: An Inter-Sectoral Approach
ANTONIOLLI, A.; HIDE, M.; GUIS, H.; HERBRETEAU, V.; BOYER, S.; CHENG, S.; NGUON, K.; SORN, S.; GUILLEBAUD, J.; AIZAWA PORTO DE ABREU, J.; HAK, S.; OEURN, K.; NOV, K.; NOUHIN, J.; HUL, V.; DUONG, V.; Karlsson, E. A.; CHHAY, S.; KONG, P.; COMMANS, F.; SAM, C.; GOV, P.; HENG, V.; SOUV, K.; SIN, S.; SIENG, T.; CANTAERT, T.; GUILLARD, B.; CAUCHEMEZ, S.; KRANG, S.; GOUTARD, F.; LY, S.; BANULS, A.-L.; Flamand, C.
Show abstract
BackgroundTropical low- and middle-income countries are highly vulnerable to zoonoses and vector-borne diseases, with risks amplified by climatic events, environmental change, and limited surveillance capacity. Cambodia is particularly exposed due to its ecological diversity, seasonal flooding, and rapidly changing land use. Globally, however, field based One Health approaches remain under-implemented, limiting practical evidence on how to address these complex threats. MethodsThis protocol describes a longitudinal One Health study conducted in three villages of Battambang province, Cambodia, designed to investigate the prevalence and transmission dynamics of zoonotic and potentially zoonotic pathogens at the human-animal-environment interface. The study examines how vector density, diversity, and pathogen circulation are influenced by hydrological variation and seasonality, and assesses the socio-demographic, behavioral, and environmental factors shaping transmission. Integrated data will be collected through serological and molecular analyses in humans and animals, environmental sampling, and entomological surveillance, enabling cross-compartmental and spatiotemporal analyses. Expected ResultsThe study will generate integrated, cross-sectoral data to characterize pathogen exposure patterns, identify high-risk populations and practices, and inform targeted public health, veterinary, and environmental interventions. ConclusionsBy sharing this protocol, the work addresses a global methodological gap in operationalizing One Health in the field and supports the development of integrated surveillance strategies in climate-sensitive, resource-limited settings.
Matching journals
The top 4 journals account for 50% of the predicted probability mass.