TY - JOUR
T1 - The Importance of Including Non-Household Environments in Dengue Vector Control Activities
AU - Peña-García, V. ctor Hugo
AU - Mutuku, Francis M.
AU - Ndenga, Bryson A.
AU - Mbakaya, Joel Omari
AU - Ndire, Samwuel Otieno
AU - Agola, Gladys Adhiambo
AU - Mutuku, Paul S.
AU - Malumbo, Said L.
AU - Ng’ang’a, Charles M.
AU - Andrews, Jason R.
AU - Mordecai, Erin A.
AU - LaBeaud, A. Desiree
N1 - Funding Information: This project was supported by NIH (R01AI102918 PI LaBeaud). A.D.L. is supported by NIH grants (R01AI102918, R01 AI149614, R01AI155959, D43TW011547 with Fogarty International Center) and the Stanford Center for Innovation in Global Health. E.A.M. is supported by NIH and National Science Foundation grants (R35GM133439, R01AI168097, R01AI102918, DEB-2011147 with Fogarty International Center), the Stanford Woods Institute for the Environment, and the Stanford Center for Innovation in Global Health. The post-doctoral fellowship of V.H.P.-G. was supported by grants R01AI102918 and R35GM133439. Publisher Copyright: © 2023 by the authors.
PY - 2023/7/1
Y1 - 2023/7/1
N2 - Most vector control activities in urban areas are focused on household environments; however, information relating to infection risks in spaces other than households is poor, and the relative risk that these spaces represent has not yet been fully understood. We used data-driven simulations to investigate the importance of household and non-household environments for dengue entomological risk in two Kenyan cities where dengue circulation has been reported. Fieldwork was performed using four strategies that targeted different stages of mosquitoes: ovitraps, larval collections, Prokopack aspiration, and BG-sentinel traps. Data were analyzed separately between household and non-household environments to assess mosquito presence, the number of vectors collected, and the risk factors for vector presence. With these data, we simulated vector and human populations to estimate the parameter m and mosquito-to-human density in both household and non-household environments. Among the analyzed variables, the main difference was found in mosquito abundance, which was consistently higher in non-household environments in Kisumu but was similar in Ukunda. Risk factor analysis suggests that small, clean water-related containers serve as mosquito breeding places in households as opposed to the trash- and rainfall-related containers found in non-household structures. We found that the density of vectors (m) was higher in non-household than household environments in Kisumu and was also similar or slightly lower between both environments in Ukunda. These results suggest that because vectors are abundant, there is a potential risk of transmission in non-household environments; hence, vector control activities should take these spaces into account.
AB - Most vector control activities in urban areas are focused on household environments; however, information relating to infection risks in spaces other than households is poor, and the relative risk that these spaces represent has not yet been fully understood. We used data-driven simulations to investigate the importance of household and non-household environments for dengue entomological risk in two Kenyan cities where dengue circulation has been reported. Fieldwork was performed using four strategies that targeted different stages of mosquitoes: ovitraps, larval collections, Prokopack aspiration, and BG-sentinel traps. Data were analyzed separately between household and non-household environments to assess mosquito presence, the number of vectors collected, and the risk factors for vector presence. With these data, we simulated vector and human populations to estimate the parameter m and mosquito-to-human density in both household and non-household environments. Among the analyzed variables, the main difference was found in mosquito abundance, which was consistently higher in non-household environments in Kisumu but was similar in Ukunda. Risk factor analysis suggests that small, clean water-related containers serve as mosquito breeding places in households as opposed to the trash- and rainfall-related containers found in non-household structures. We found that the density of vectors (m) was higher in non-household than household environments in Kisumu and was also similar or slightly lower between both environments in Ukunda. These results suggest that because vectors are abundant, there is a potential risk of transmission in non-household environments; hence, vector control activities should take these spaces into account.
KW - Aedes aegypti
KW - households
KW - non-household environments
KW - simulations
KW - vector sampling
KW - vectorial capacity
UR - http://www.scopus.com/inward/record.url?scp=85165953636&partnerID=8YFLogxK
U2 - https://doi.org/10.3390/v15071550
DO - https://doi.org/10.3390/v15071550
M3 - Article
C2 - 37515236
SN - 1999-4915
VL - 15
JO - Viruses
JF - Viruses
IS - 7
M1 - 1550
ER -