In many developing countries where pathogenic diseases of animal waste origin, such as giardiasis and cryptosporidiosis, are often prevalent, facilities are limited to treat livestock waste. However, household-scale anaerobic digesters are currently being promoted for bioenergy production from livestock manure. Since the effluent is often used as a fertilizer for food crops, it is critical to understand the effect of environmental conditions within household-scale digesters on the viability of Cryptosporidium parvum oocysts and Giardia lamblia cysts. In this study, key environmental parameters affecting (oo)cyst inactivation were measured in four tubular anaerobic digesters, which are a type of household-scale digester promoted for treatment of swine waste in rural Costa Rica. Interviews and participant observations were used to understand digester operation and maintenance procedures. Ambient temperatures (21-24°C), near-neutral pH, total ammonia nitrogen (TAN) concentrations<250 mg/L and hydraulic retention times (HRTs) between 23 and 180 days were observed. Laboratory (oo)cysts inactivation studies were performed in bench-scale digesters, which were maintained under conditions similar to those observed in the field. Apparent first-order inactivation rate coefficients for Giardia lamblia and Cryptosporidium parvum were 0.155 ± 0.041 and 0.054 ± 0.006 day(-1), respectively. Temperature and volatile fatty acids were the main factors contributing to Cryptosporidium parvum and Giardia lamblia inactivation. A mathematical model was developed that predicts the concentration of (oo)cysts in the liquid effluent of tubular digesters like those observed in Costa Rica. A mathematical model was developed that predicts the concentration of (oo)cysts in the liquid effluent of tubular digesters like those observed in Costa Rica. Two dimensionless groups can be used to predict the performance of the digesters for inactivating pathogens; both dimensionless groups depend upon the average HRT in the digester. This is the first study to combine mathematical modeling with qualitative analysis, field and laboratory studies to predict the concentrations of (oo)cysts in tubular digester effluents.