Optimizing Costs: How Biosecurity Measures Transform Smallholder Poultry Economics

Attempts to manage poultry diseases through clinical treatment are both costly and increase the risk of antimicrobial resistance (AMR). This study was motivated by the need to tackle the dual challenge of diseases leading to AMR and low poultry productivity in Sub-Saharan Africa. It assesses the cost efficiency of farmers who use varying levels of biosecurity measures. We employ a three-step estimation procedure: first, a latent class analysis (LCA) model to describe adoption patterns. Secondly, a stochastic frontier analysis is used to generate cost efficiency scores and inefficiency effects. Lastly, a one-way ANOVA is used to compare cost efficiency by adoption categories. The LCA model reveals three uptake patterns for biosecurity measures with low, moderate, and high adoption behaviors. The average cost efficiency scores are 49.5%, 61.6%, and 68.6%, respectively, for the low, moderate, and high adoption categories. The overall score of 60.4% indicates that poultry farmers in Nyanza are largely cost-efficient. We demonstrate from the observed pattern that there is room to improve cost performance through increased use of biosecurity measures. Years of experience in poultry farming and larger stock sizes reduce farm cost inefficiency. These findings form the basis for the promotion of biosecurity measures

Community-based intermittent mass testing and treatment for malaria in an area of high transmission intensity, western Kenya: study design and methodology for a cluster randomized controlled trial

Abstract Most human Plasmodium infections in western Kenya are asymptomatic and are believed to contribute importantly to malaria transmission. Elimination of asymptomatic infections requires active treatment approaches, such as mass testing and treatment (MTaT) or mass drug administration (MDA), as infected persons do not seek care for their infection. Evaluations of community-based approaches that are designed to reduce malaria transmission require careful attention to study design to ensure that important effects can be measured accurately. This manuscript describes the study design and methodology of a cluster-randomized controlled trial to evaluate a MTaT approach for malaria transmission reduction in an area of high malaria transmission. Ten health facilities in western Kenya were purposively selected for inclusion. The communities within 3 km of each health facility were divided into three clusters of approximately equal population size. Two clusters around each health facility were randomly assigned to the control arm, and one to the intervention arm. Three times per year for 2 years, after the long and short rains, and again before the long rains, teams of community health volunteers visited every household within the intervention arm, tested all consenting individuals with malaria rapid diagnostic tests, and treated all positive individuals with an effective anti-malarial. The effect of mass testing and treatment on malaria transmission was measured through population-based longitudinal cohorts, outpatient visits for clinical malaria, periodic population-based cross-sectional surveys, and entomological indices

Additional file 1 of Novel application of one-step pooled molecular testing and maximum likelihood approaches to estimate the prevalence of malaria parasitaemia among rapid diagnostic test negative samples in western Kenya

Additional file 1. Methods for sample size determination and sampling weights