Temporal variability in water quality as a driver of microbial and parasitic infections in smallholder aquaculture systems

Aquaculture’s productivity is often constrained by disease events linked to suboptimal water quality, yet longitudinal, farm-level evidence from smallholder systems remains limited. We evaluated how pond water quality influences microbial and parasitic infestations using monthly observations across 13 ponds on 5 farms in Uasin Gishu County, Kenya (May 2023 to April 2024). Physicochemical parameters (temperature, dissolved oxygen [DO], pH, turbidity, conductivity, nutrients, biological oxygen demand [BOD], chemical oxygen demand [COD], total dissolved solids [TDS]) were measured alongside total bacterial counts and parasite screenings of fish. Data were analyzed at the pond-month level using correlation tests and logistic regression to identify predictors of infection. Seasonal shifts in water quality aligned closely with disease patterns. Higher BOD/COD and turbidity were associated with elevated bacterial loads, whereas higher temperature and DO generally corresponded to reduced bacterial counts. Parasite occurrence showed taxon-specific environmental responses; for example, Dactylogyrus spp. and Clinostomum spp. were linked to variation in TDS, nitrates, pH, and temperature. Multivariate models identified ammonia/nitrite, DO, turbidity, and organic load (BOD/COD) as consistent predictors of infection risk, demonstrating that temporal water quality dynamics, not location alone, drive disease pressure in smallholder ponds. These findings highlight the strong interplay between environmental variables and fish health in aquaculture systems. In particular, interventions such as improved water quality management and routine monitoring of nutrient dynamics could substantially reduce disease burdens, improve farm yields, and ensure sustainable fish farming. Importantly, the results extend beyond local relevance: they highlight how integrating seasonal water quality monitoring into smallholder aquaculture can generate transferable insights for disease prevention in other data-limited regions.