| Sumario: | Finding vector infestations in low prevalence settings is difficult but can be facilitated through rational use of historical vector information. However, health workers make decisions in the field based on perceptions and experience and may alter the potential efficacy of algorithms. In Arequipa, Peru, after a long spraying campaign for controlling Chagas disease, very few houses are infested with Triatoma infestans. Our aim was to compare alternative vector surveillance approaches: 1) Houses are assigned for inspection by a computer; 2) Inspectors are incentivized to choose high risk houses based on a modeling-generated risk map; 3) Current practice--inspectors choose houses with little or no prior information. These approaches were developed using the methodology accordingly: 1) based on a computerized algorithm, optimizing spatial coverage of higher risk houses, participants were told where to go, 2) using a behavioral economics approach to improve the participants' use of a risk map, and finally 3) the current practice using participants’ experience. The nine participants entered data with a mobile app and searched 54 areas.
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