Human vs computational algorithms in vector surveillance for cities
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, P...
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2022
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| Acceso en línea: | http://sedici.unlp.edu.ar/handle/10915/155989 |
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I19-R120-10915-155989 |
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I19-R120-10915-1559892023-08-07T20:01:44Z http://sedici.unlp.edu.ar/handle/10915/155989 Human vs computational algorithms in vector surveillance for cities Arévalo Nieto, Claudia Sheen, Justin Condori Pino, Carlos Condori Luna, Gian Franco Shinnik, Julianna Peterson, Jeni Castillo Neyra, Ricardo Levy, Michael Z. 2022-11-03 2022 2023-08-07T15:00:56Z en Ciencias Naturales Chagas vector control surveillance 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. Para acceder a la videoconferencia completa, hacer clic en "Enlace externo". Sociedad Latinoamericana de Ecología de Vectores Objeto de conferencia Objeto de conferencia http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) application/pdf |
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Universidad Nacional de La Plata |
| institution_str |
I-19 |
| repository_str |
R-120 |
| collection |
SEDICI (UNLP) |
| language |
Inglés |
| topic |
Ciencias Naturales Chagas vector control surveillance |
| spellingShingle |
Ciencias Naturales Chagas vector control surveillance Arévalo Nieto, Claudia Sheen, Justin Condori Pino, Carlos Condori Luna, Gian Franco Shinnik, Julianna Peterson, Jeni Castillo Neyra, Ricardo Levy, Michael Z. Human vs computational algorithms in vector surveillance for cities |
| topic_facet |
Ciencias Naturales Chagas vector control surveillance |
| description |
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. |
| format |
Objeto de conferencia Objeto de conferencia |
| author |
Arévalo Nieto, Claudia Sheen, Justin Condori Pino, Carlos Condori Luna, Gian Franco Shinnik, Julianna Peterson, Jeni Castillo Neyra, Ricardo Levy, Michael Z. |
| author_facet |
Arévalo Nieto, Claudia Sheen, Justin Condori Pino, Carlos Condori Luna, Gian Franco Shinnik, Julianna Peterson, Jeni Castillo Neyra, Ricardo Levy, Michael Z. |
| author_sort |
Arévalo Nieto, Claudia |
| title |
Human vs computational algorithms in vector surveillance for cities |
| title_short |
Human vs computational algorithms in vector surveillance for cities |
| title_full |
Human vs computational algorithms in vector surveillance for cities |
| title_fullStr |
Human vs computational algorithms in vector surveillance for cities |
| title_full_unstemmed |
Human vs computational algorithms in vector surveillance for cities |
| title_sort |
human vs computational algorithms in vector surveillance for cities |
| publishDate |
2022 |
| url |
http://sedici.unlp.edu.ar/handle/10915/155989 |
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