Background: Heterogeneity in malaria transmission has household,temporal, and spatial components. These factors are relevant forimproving the efficiency of malaria control by targeting heterogeneity.To quantify variation, we analyzed mosquito counts fromentomological surveillance conducted at three study sites in Ugandathat varied in malaria transmission intensity. Mosquito biting orexposure is a risk factor for malaria transmission.Methods: Using a Bayesian zero-inflated negative binomial model,validated via a comprehensive simulation study, we quantifiedhousehold differences in malaria vector density and examined itsspatial distribution. We introduced a novel approach for identifyingchanges in vector abundance hotspots over time by computing theGetis-Ord statistic on ratios of household biting propensities fordifferent scenarios. We also explored the association of householdbiting propensities with housing and environmental covariates.Results: In each site, there was evidence for hot and cold spots ofvector abundance, and spatial patterns associated with urbanicity,elevation, or other environmental covariates. We found somedifferences in the hotspots in rainy vs. dry seasons or before vs. afterthe application of control interventions. Housing quality explained aportion of the variation among households in mosquito counts.Conclusion: This work provided an improved understanding ofheterogeneity in malaria vector density at the three study sites inUganda and offered a valuable opportunity for assessing whetherinterventions could be spatially targeted to be aimed at abundancehotspots which may increase malaria risk. Indoor residual sprayingwas shown to be a successful measure of vector control interventionsin Tororo, Uganda. Cement walls, brick floors, closed eaves, screenedairbricks, and tiled roofs were features of a house that had shownreduction of household biting propensity. Improvements in housequality should be recommended as a supplementary measure formalaria control reducing risk of infection.KeywordsHeterogeneity, hotspots, housing, malaria vectors, spatial, zero-inflated negative binomial