Who is missed in a community-based survey: Assessment and implications of biases due to incomplete sampling frame in a community-based serosurvey, Choma and Ndola Districts, Zambia, 2022.

Community-based serological studies are increasingly relied upon to measure disease burden, identify population immunity gaps, and guide control and elimination strategies; however, there is little understanding of the potential for and impact of sampling biases on outcomes of interest. As part of e...

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Main Authors: Natalya Kostandova (Author), Simon Mutembo (Author), Christine Prosperi (Author), Francis Dien Mwansa (Author), Chola Nakazwe (Author), Harriet Namukoko (Author), Bertha Nachinga (Author), Gershom Chongwe (Author), Innocent Chilumba (Author), Kalumbu H Matakala (Author), Gloria Musukwa (Author), Mutinta Hamahuwa (Author), Webster Mufwambi (Author), Japhet Matoba (Author), Kenny Situtu (Author), Irene Mutale (Author), Alex C Kong (Author), Edgar Simulundu (Author), Phillimon Ndubani (Author), Alvira Z Hasan (Author), Shaun A Truelove (Author), Amy K Winter (Author), Andrea C Carcelen (Author), Bryan Lau (Author), William J Moss (Author), Amy Wesolowski (Author)
Format: Book
Published: Public Library of Science (PLoS), 2024-01-01T00:00:00Z.
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100 1 0 |a Natalya Kostandova  |e author 
700 1 0 |a Simon Mutembo  |e author 
700 1 0 |a Christine Prosperi  |e author 
700 1 0 |a Francis Dien Mwansa  |e author 
700 1 0 |a Chola Nakazwe  |e author 
700 1 0 |a Harriet Namukoko  |e author 
700 1 0 |a Bertha Nachinga  |e author 
700 1 0 |a Gershom Chongwe  |e author 
700 1 0 |a Innocent Chilumba  |e author 
700 1 0 |a Kalumbu H Matakala  |e author 
700 1 0 |a Gloria Musukwa  |e author 
700 1 0 |a Mutinta Hamahuwa  |e author 
700 1 0 |a Webster Mufwambi  |e author 
700 1 0 |a Japhet Matoba  |e author 
700 1 0 |a Kenny Situtu  |e author 
700 1 0 |a Irene Mutale  |e author 
700 1 0 |a Alex C Kong  |e author 
700 1 0 |a Edgar Simulundu  |e author 
700 1 0 |a Phillimon Ndubani  |e author 
700 1 0 |a Alvira Z Hasan  |e author 
700 1 0 |a Shaun A Truelove  |e author 
700 1 0 |a Amy K Winter  |e author 
700 1 0 |a Andrea C Carcelen  |e author 
700 1 0 |a Bryan Lau  |e author 
700 1 0 |a William J Moss  |e author 
700 1 0 |a Amy Wesolowski  |e author 
245 0 0 |a Who is missed in a community-based survey: Assessment and implications of biases due to incomplete sampling frame in a community-based serosurvey, Choma and Ndola Districts, Zambia, 2022. 
260 |b Public Library of Science (PLoS),   |c 2024-01-01T00:00:00Z. 
500 |a 2767-3375 
500 |a 10.1371/journal.pgph.0003072 
520 |a Community-based serological studies are increasingly relied upon to measure disease burden, identify population immunity gaps, and guide control and elimination strategies; however, there is little understanding of the potential for and impact of sampling biases on outcomes of interest. As part of efforts to quantify measles immunity gaps in Zambia, a community-based serological survey using stratified multi-stage cluster sampling approach was conducted in Ndola and Choma districts in May-June 2022, enrolling 1245 individuals. We carried out a follow-up study among individuals missed from the sampling frame of the serosurvey in July-August 2022, enrolling 672 individuals. We assessed the potential for and impact of biases in the community-based serosurvey by i) estimating differences in characteristics of households and individuals included and excluded (77% vs 23% of households) from the sampling frame of the serosurvey and ii) evaluating the magnitude these differences make on healthcare-seeking behavior, vaccination coverage, and measles seroprevalence. We found that missed households were 20% smaller and 25% less likely to have children. Missed individuals resided in less wealthy households, had different distributions of sex and occupation, and were more likely to seek care at health facilities. Despite these differences, simulating a survey in which missed households were included in the sampling frame resulted in less than a 5% estimated bias in these outcomes. Although community-based studies are upheld as the gold standard study design in assessing immunity gaps and underlying community health characteristics, these findings underscore the fact that sampling biases can impact the results of even well-conducted community-based surveys. Results from these studies should be interpreted in the context of the study methodology and challenges faced during implementation, which include shortcomings in establishing accurate and up-to-date sampling frames. Failure to account for these shortcomings may result in biased estimates and detrimental effects on decision-making. 
546 |a EN 
690 |a Public aspects of medicine 
690 |a RA1-1270 
655 7 |a article  |2 local 
786 0 |n PLOS Global Public Health, Vol 4, Iss 4, p e0003072 (2024) 
787 0 |n https://doi.org/10.1371/journal.pgph.0003072 
787 0 |n https://doaj.org/toc/2767-3375 
856 4 1 |u https://doaj.org/article/9dde86dbdd7b45eda5ec804e1744a21d  |z Connect to this object online.