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Estimating malaria transmission risk through surveillance of human–vector interactions in northern Ghana

BACKGROUND: Vector bionomics are important aspects of vector-borne disease control programs. Mosquito-biting risks are affected by environmental, mosquito behavior and human factors, which are important for assessing exposure risk and intervention impacts. This study estimated malaria transmission r...

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Autores principales: Coleman, Sylvester, Yihdego, Yemane, Gyamfi, Frank, Kolyada, Lena, Tongren, Jon Eric, Zigirumugabe, Sixte, Dery, Dominic B., Badu, Kingsley, Obiri-Danso, Kwasi, Boakye, Daniel, Szumlas, Daniel, Armistead, Jennifer S., Dadzie, Samuel K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10280856/
https://www.ncbi.nlm.nih.gov/pubmed/37337221
http://dx.doi.org/10.1186/s13071-023-05793-2
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author Coleman, Sylvester
Yihdego, Yemane
Gyamfi, Frank
Kolyada, Lena
Tongren, Jon Eric
Zigirumugabe, Sixte
Dery, Dominic B.
Badu, Kingsley
Obiri-Danso, Kwasi
Boakye, Daniel
Szumlas, Daniel
Armistead, Jennifer S.
Dadzie, Samuel K.
author_facet Coleman, Sylvester
Yihdego, Yemane
Gyamfi, Frank
Kolyada, Lena
Tongren, Jon Eric
Zigirumugabe, Sixte
Dery, Dominic B.
Badu, Kingsley
Obiri-Danso, Kwasi
Boakye, Daniel
Szumlas, Daniel
Armistead, Jennifer S.
Dadzie, Samuel K.
author_sort Coleman, Sylvester
collection PubMed
description BACKGROUND: Vector bionomics are important aspects of vector-borne disease control programs. Mosquito-biting risks are affected by environmental, mosquito behavior and human factors, which are important for assessing exposure risk and intervention impacts. This study estimated malaria transmission risk based on vector–human interactions in northern Ghana, where indoor residual spraying (IRS) and insecticide-treated nets (ITNs) have been deployed. METHODS: Indoor and outdoor human biting rates (HBRs) were measured using monthly human landing catches (HLCs) from June 2017 to April 2019. Mosquitoes collected were identified to species level, and Anopheles gambiae sensu lato (An. gambiae s.l.) samples were examined for parity and infectivity. The HBRs were adjusted using mosquito parity and human behavioral observations. RESULTS: Anopheles gambiae was the main vector species in the IRS (81%) and control (83%) communities. Indoor and outdoor HBRs were similar in both the IRS intervention (10.6 vs. 11.3 bites per person per night [b/p/n]; z = −0.33, P = 0.745) and control communities (18.8 vs. 16.4 b/p/n; z = 1.57, P = 0.115). The mean proportion of parous An. gambiae s.l. was lower in IRS communities (44.6%) than in control communities (71.7%). After adjusting for human behavior observations and parity, the combined effect of IRS and ITN utilization (IRS: 37.8%; control: 57.3%) on reducing malaria transmission risk was 58% in IRS + ITN communities and 27% in control communities with ITNs alone (z = −4.07, P < 0.001). However, this also revealed that about 41% and 31% of outdoor adjusted bites in IRS and control communities respectively, occurred before bed time (10:00 pm). The mean directly measured annual entomologic inoculation rates (EIRs) during the study were 6.1 infective bites per person per year (ib/p/yr) for IRS communities and 16.3 ib/p/yr for control communities. After considering vector survival and observed human behavior, the estimated EIR for IRS communities was 1.8 ib/p/yr, which represents about a 70% overestimation of risk compared to the directly measured EIR; for control communities, it was 13.6 ib/p/yr (16% overestimation). CONCLUSION: Indoor residual spraying significantly impacted entomological indicators of malaria transmission. The results of this study indicate that vector bionomics alone do not provide an accurate assessment of malaria transmission exposure risk. By accounting for human behavior parameters, we found that high coverage of ITNs alone had less impact on malaria transmission indices than combining ITNs with IRS, likely due to observed low net use. Reinforcing effective communication for behavioral change in net use and IRS could further reduce malaria transmission. GRAPHICAL ABSTRACT: [Image: see text] SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13071-023-05793-2.
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spelling pubmed-102808562023-06-21 Estimating malaria transmission risk through surveillance of human–vector interactions in northern Ghana Coleman, Sylvester Yihdego, Yemane Gyamfi, Frank Kolyada, Lena Tongren, Jon Eric Zigirumugabe, Sixte Dery, Dominic B. Badu, Kingsley Obiri-Danso, Kwasi Boakye, Daniel Szumlas, Daniel Armistead, Jennifer S. Dadzie, Samuel K. Parasit Vectors Research BACKGROUND: Vector bionomics are important aspects of vector-borne disease control programs. Mosquito-biting risks are affected by environmental, mosquito behavior and human factors, which are important for assessing exposure risk and intervention impacts. This study estimated malaria transmission risk based on vector–human interactions in northern Ghana, where indoor residual spraying (IRS) and insecticide-treated nets (ITNs) have been deployed. METHODS: Indoor and outdoor human biting rates (HBRs) were measured using monthly human landing catches (HLCs) from June 2017 to April 2019. Mosquitoes collected were identified to species level, and Anopheles gambiae sensu lato (An. gambiae s.l.) samples were examined for parity and infectivity. The HBRs were adjusted using mosquito parity and human behavioral observations. RESULTS: Anopheles gambiae was the main vector species in the IRS (81%) and control (83%) communities. Indoor and outdoor HBRs were similar in both the IRS intervention (10.6 vs. 11.3 bites per person per night [b/p/n]; z = −0.33, P = 0.745) and control communities (18.8 vs. 16.4 b/p/n; z = 1.57, P = 0.115). The mean proportion of parous An. gambiae s.l. was lower in IRS communities (44.6%) than in control communities (71.7%). After adjusting for human behavior observations and parity, the combined effect of IRS and ITN utilization (IRS: 37.8%; control: 57.3%) on reducing malaria transmission risk was 58% in IRS + ITN communities and 27% in control communities with ITNs alone (z = −4.07, P < 0.001). However, this also revealed that about 41% and 31% of outdoor adjusted bites in IRS and control communities respectively, occurred before bed time (10:00 pm). The mean directly measured annual entomologic inoculation rates (EIRs) during the study were 6.1 infective bites per person per year (ib/p/yr) for IRS communities and 16.3 ib/p/yr for control communities. After considering vector survival and observed human behavior, the estimated EIR for IRS communities was 1.8 ib/p/yr, which represents about a 70% overestimation of risk compared to the directly measured EIR; for control communities, it was 13.6 ib/p/yr (16% overestimation). CONCLUSION: Indoor residual spraying significantly impacted entomological indicators of malaria transmission. The results of this study indicate that vector bionomics alone do not provide an accurate assessment of malaria transmission exposure risk. By accounting for human behavior parameters, we found that high coverage of ITNs alone had less impact on malaria transmission indices than combining ITNs with IRS, likely due to observed low net use. Reinforcing effective communication for behavioral change in net use and IRS could further reduce malaria transmission. GRAPHICAL ABSTRACT: [Image: see text] SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13071-023-05793-2. BioMed Central 2023-06-19 /pmc/articles/PMC10280856/ /pubmed/37337221 http://dx.doi.org/10.1186/s13071-023-05793-2 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Coleman, Sylvester
Yihdego, Yemane
Gyamfi, Frank
Kolyada, Lena
Tongren, Jon Eric
Zigirumugabe, Sixte
Dery, Dominic B.
Badu, Kingsley
Obiri-Danso, Kwasi
Boakye, Daniel
Szumlas, Daniel
Armistead, Jennifer S.
Dadzie, Samuel K.
Estimating malaria transmission risk through surveillance of human–vector interactions in northern Ghana
title Estimating malaria transmission risk through surveillance of human–vector interactions in northern Ghana
title_full Estimating malaria transmission risk through surveillance of human–vector interactions in northern Ghana
title_fullStr Estimating malaria transmission risk through surveillance of human–vector interactions in northern Ghana
title_full_unstemmed Estimating malaria transmission risk through surveillance of human–vector interactions in northern Ghana
title_short Estimating malaria transmission risk through surveillance of human–vector interactions in northern Ghana
title_sort estimating malaria transmission risk through surveillance of human–vector interactions in northern ghana
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10280856/
https://www.ncbi.nlm.nih.gov/pubmed/37337221
http://dx.doi.org/10.1186/s13071-023-05793-2
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