Assessing trends in non-coverage bias in mobile phone surveys for estimating insecticide-treated net coverage: a cross-sectional analysis in Tanzania, 2007–2017
Introduction Monitoring insecticide-treated net (ITN) coverage and use generally relies on household surveys which occur on a relatively infrequent basis. Because indicators of coverage are used to forecast the need for ITNs and aid in planning ITN distribution campaigns, higher frequency monitoring...
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BMJ Publishing Group
2025-04-01
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| Series: | BMJ Public Health |
| Online Access: | https://bmjpublichealth.bmj.com/content/3/1/e001379.full |
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| author | Matt Worges Ruth A Ashton Janna Wisniewski Paul Hutchinson Hannah Koenker Tory Taylor Hannah Metcalfe Ester Elisaria Mponeja P Gitanya Charles Dismas Mwalimu Frank Chacky Joshua O Yukich |
| author_facet | Matt Worges Ruth A Ashton Janna Wisniewski Paul Hutchinson Hannah Koenker Tory Taylor Hannah Metcalfe Ester Elisaria Mponeja P Gitanya Charles Dismas Mwalimu Frank Chacky Joshua O Yukich |
| author_sort | Matt Worges |
| collection | DOAJ |
| description | Introduction Monitoring insecticide-treated net (ITN) coverage and use generally relies on household surveys which occur on a relatively infrequent basis. Because indicators of coverage are used to forecast the need for ITNs and aid in planning ITN distribution campaigns, higher frequency monitoring could be helpful to guide programme strategies. The use of mobile phone-based survey (MPS) strategies in low-income and middle-income countries has emerged as a rapid and comparatively inexpensive complement to large-scale population-based household surveys, considering the dramatic growth trend of mobile phone ownership.Methods The potential for non-coverage bias in the calculation of ITN coverage estimates from MPSs was assessed through the use of five consecutive Tanzania-specific Demographic and Health Surveys (DHS). Primary comparisons were made between all households included in the data sets (the reference standard) and mobile phone-owning households (the comparator). Deviations in ITN coverage estimates between the reference standard and mobile phone-owning households were used as a proxy for assessing potential non-coverage bias, with estimates calculated using a bootstrap method.Results By the 2017 DHS, regional measures of non-coverage bias for ITN coverage indicators rarely exceeded a ±3 percentage point difference when comparing mobile phone-owning households to the overall sample. However, larger differences were observed when comparing mobile phone-owning households to non-mobile phone-owning households, particularly in periods without recent mass ITN distributions.Conclusion Results suggest that MPSs can reliably estimate ITN coverage at the population level when both ITN coverage and mobile phone ownership are high. However, as ITN coverage declines, the gap between phone-owning and non-phone-owning households widens, indicating potential non-coverage bias and underscoring the need for caution in interpreting MPS data under such conditions. |
| format | Article |
| id | doaj-art-6b4d5a6adea94b87b3fdcd07ae7a185e |
| institution | DOAJ |
| issn | 2753-4294 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | BMJ Publishing Group |
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| series | BMJ Public Health |
| spelling | doaj-art-6b4d5a6adea94b87b3fdcd07ae7a185e2025-08-20T03:16:05ZengBMJ Publishing GroupBMJ Public Health2753-42942025-04-013110.1136/bmjph-2024-001379Assessing trends in non-coverage bias in mobile phone surveys for estimating insecticide-treated net coverage: a cross-sectional analysis in Tanzania, 2007–2017Matt Worges0Ruth A Ashton1Janna Wisniewski2Paul Hutchinson3Hannah Koenker4Tory Taylor5Hannah Metcalfe6Ester Elisaria7Mponeja P Gitanya8Charles Dismas Mwalimu9Frank Chacky10Joshua O Yukich11Tropical Health, New Orleans, Louisiana, USATulane University School of Public Health and Tropical Medicine, New Orleans, Louisiana, USATulane University School of Public Health and Tropical Medicine, New Orleans, Louisiana, USATulane University School of Public Health and Tropical Medicine, New Orleans, Louisiana, USATropical Health LLP, Baltimore, Maryland, USAThe University of North Carolina, Carolina Population Center, Chapel Hill, North Carolina, USAViamo, Dar es Salaam, Tanzania, United Republic ofDepartment of Impact Evaluation, Ifakara Health Institute, Ifakara, Dar es Salaam, Tanzania, United Republic ofNational Malaria Control Program, Ministry of Health, Dodoma, Tanzania, United Republic ofNational Malaria Control Program, Ministry of Health, Dodoma, Tanzania, United Republic ofNational Malaria Control Program, Ministry of Health, Dodoma, Tanzania, United Republic ofTulane University School of Public Health and Tropical Medicine, New Orleans, Louisiana, USAIntroduction Monitoring insecticide-treated net (ITN) coverage and use generally relies on household surveys which occur on a relatively infrequent basis. Because indicators of coverage are used to forecast the need for ITNs and aid in planning ITN distribution campaigns, higher frequency monitoring could be helpful to guide programme strategies. The use of mobile phone-based survey (MPS) strategies in low-income and middle-income countries has emerged as a rapid and comparatively inexpensive complement to large-scale population-based household surveys, considering the dramatic growth trend of mobile phone ownership.Methods The potential for non-coverage bias in the calculation of ITN coverage estimates from MPSs was assessed through the use of five consecutive Tanzania-specific Demographic and Health Surveys (DHS). Primary comparisons were made between all households included in the data sets (the reference standard) and mobile phone-owning households (the comparator). Deviations in ITN coverage estimates between the reference standard and mobile phone-owning households were used as a proxy for assessing potential non-coverage bias, with estimates calculated using a bootstrap method.Results By the 2017 DHS, regional measures of non-coverage bias for ITN coverage indicators rarely exceeded a ±3 percentage point difference when comparing mobile phone-owning households to the overall sample. However, larger differences were observed when comparing mobile phone-owning households to non-mobile phone-owning households, particularly in periods without recent mass ITN distributions.Conclusion Results suggest that MPSs can reliably estimate ITN coverage at the population level when both ITN coverage and mobile phone ownership are high. However, as ITN coverage declines, the gap between phone-owning and non-phone-owning households widens, indicating potential non-coverage bias and underscoring the need for caution in interpreting MPS data under such conditions.https://bmjpublichealth.bmj.com/content/3/1/e001379.full |
| spellingShingle | Matt Worges Ruth A Ashton Janna Wisniewski Paul Hutchinson Hannah Koenker Tory Taylor Hannah Metcalfe Ester Elisaria Mponeja P Gitanya Charles Dismas Mwalimu Frank Chacky Joshua O Yukich Assessing trends in non-coverage bias in mobile phone surveys for estimating insecticide-treated net coverage: a cross-sectional analysis in Tanzania, 2007–2017 BMJ Public Health |
| title | Assessing trends in non-coverage bias in mobile phone surveys for estimating insecticide-treated net coverage: a cross-sectional analysis in Tanzania, 2007–2017 |
| title_full | Assessing trends in non-coverage bias in mobile phone surveys for estimating insecticide-treated net coverage: a cross-sectional analysis in Tanzania, 2007–2017 |
| title_fullStr | Assessing trends in non-coverage bias in mobile phone surveys for estimating insecticide-treated net coverage: a cross-sectional analysis in Tanzania, 2007–2017 |
| title_full_unstemmed | Assessing trends in non-coverage bias in mobile phone surveys for estimating insecticide-treated net coverage: a cross-sectional analysis in Tanzania, 2007–2017 |
| title_short | Assessing trends in non-coverage bias in mobile phone surveys for estimating insecticide-treated net coverage: a cross-sectional analysis in Tanzania, 2007–2017 |
| title_sort | assessing trends in non coverage bias in mobile phone surveys for estimating insecticide treated net coverage a cross sectional analysis in tanzania 2007 2017 |
| url | https://bmjpublichealth.bmj.com/content/3/1/e001379.full |
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