Estimation of bed net coverage indicators in Tanzania using mobile phone surveys: a comparison of sampling approaches

• Published in: Malaria Journal
• Main Authors: Matt Worges, Benjamin Kamala, Joshua Yukich, Frank Chacky, Samwel Lazaro, Charles Dismas, Sijenun Aroun, Raya Ibrahim, Mwinyi Khamis, Mponeja P. Gitanya, Deodatus Mwingizi, Hannah Metcalfe, Willhard Bantanuka, Sena Deku, David Dadi, Naomi Serbantez, Dana Loll, Hannah Koenker
• Format: Article in Journal/Newspaper
• Language: English
• Published: BMC 2022
• Subjects: ITN; Mobile phone survey; Random digit dial; Coverage indicators; Tanzania; Arctic medicine. Tropical medicine; RC955-962; Infectious and parasitic diseases; RC109-216; Arctic
• Online Access: https://doi.org/10.1186/s12936-022-04408-y; https://doaj.org/article/908c86e4fc4b4c90bee701ab8172e52c

Abstract Background Threats to maintaining high population access with effective bed nets persist due to errors in quantification, bed net wear and tear, and inefficiencies in distribution activities. Monitoring bed net coverage is therefore critical, but usually occurs every 2–3 years through expensive, large-scale household surveys. Mobile phone-based survey methodologies are emerging as an alternative to household surveys and can provide rapid estimates of coverage, however, little research on varied sampling approaches has been conducted in sub-Saharan Africa. Methods A nationally and regionally representative cross-sectional mobile phone survey was conducted in early 2021 in Tanzania with focus on bed net ownership and access. Half the target sample was contacted through a random digit dial methodology (n = 3500) and the remaining half was reached through a voluntary opt-in respondent pool (n = 3500). Both sampling approaches used an interactive voice response survey. Standard RBM-MERG bed net indicators and AAPOR call metrics were calculated. In addition, the results of the two sampling approaches were compared. Results Population access (i.e., the percent of the population that could sleep under a bed net, assuming one bed net per two people) varied from a regionally adjusted low of 48.1% (Katavi) to a high of 65.5% (Dodoma). The adjusted percent of households that had a least one bed net ranged from 54.8% (Pemba) to 75.5% (Dodoma); the adjusted percent of households with at least one bed net per 2 de facto household population ranged from 35.9% (Manyara) to 55.7% (Dodoma). The estimates produced by both sampling approaches were generally similar, differing by only a few percentage points. An analysis of differences between estimates generated from the two sampling approaches showed minimal bias when considering variation across the indicator for households with at least one bed net per two de facto household population. Conclusion The results generated by this survey show that overall bed net access in ...