BACKGROUND: Household surveys are an essential tool for vaccine coverage monitoring in developing countries, and the World Health Organization (WHO) Expanded Program on Immunization (EPI) cluster survey design has been a default choice for decades. In response to methodological limitations of the traditional EPI sampling, alternative methods have been proposed, based on modern statistical and geographical techniques. This study compared the coverage estimates and the time efficiency of the EPI sampling design and two alternative methods: the compact segment sampling and innovative grid-based geographical information system (GIS) sampling. METHODS: We conducted a series of equal-sized concurrent prospective vaccine coverage surveys in Karachi, Pakistan, from January to December 2016, using traditional EPI, compact segment and grid-based GIS sampling methods. RESULTS: No differences in vaccine coverage estimates were identified across sampling methods in the peri-urban setting; however, due to stronger clustering effects and correct incorporation of sampling weights, the compact segment [design effect (DEFF) = 2.03] and the grid-based GIS surveys (DEFF = 1.72) had higher design effects and, therefore, appeared to have lower statistical precision than the traditional EPI surveys (DEFF = 1.57). To achieve the same level of apparent precision, data collection activities in the compact segment surveys would require more than twice the implementation time needed compared with the traditional EPI surveys. CONCLUSIONS: The precision of the EPI surveys appeared higher than that of the alternative methods because, under a questionable self-weighting assumption, the estimated design effect did not account for variable sampling weights. The compact segment and grid-based GIS methods were designed to improve randomness and representativeness of sampling households. Although these alternative methods did not result in coverage estimates that differed from the EPI survey results in the peri-urban setting, they have a lower risk of selection bias and therefore may be preferred.
BACKGROUND: Household surveys are an essential tool for vaccine coverage monitoring in developing countries, and the World Health Organization (WHO) Expanded Program on Immunization (EPI) cluster survey design has been a default choice for decades. In response to methodological limitations of the traditional EPI sampling, alternative methods have been proposed, based on modern statistical and geographical techniques. This study compared the coverage estimates and the time efficiency of the EPI sampling design and two alternative methods: the compact segment sampling and innovative grid-based geographical information system (GIS) sampling. METHODS: We conducted a series of equal-sized concurrent prospective vaccine coverage surveys in Karachi, Pakistan, from January to December 2016, using traditional EPI, compact segment and grid-based GIS sampling methods. RESULTS: No differences in vaccine coverage estimates were identified across sampling methods in the peri-urban setting; however, due to stronger clustering effects and correct incorporation of sampling weights, the compact segment [design effect (DEFF) = 2.03] and the grid-based GIS surveys (DEFF = 1.72) had higher design effects and, therefore, appeared to have lower statistical precision than the traditional EPI surveys (DEFF = 1.57). To achieve the same level of apparent precision, data collection activities in the compact segment surveys would require more than twice the implementation time needed compared with the traditional EPI surveys. CONCLUSIONS: The precision of the EPI surveys appeared higher than that of the alternative methods because, under a questionable self-weighting assumption, the estimated design effect did not account for variable sampling weights. The compact segment and grid-based GIS methods were designed to improve randomness and representativeness of sampling households. Although these alternative methods did not result in coverage estimates that differed from the EPI survey results in the peri-urban setting, they have a lower risk of selection bias and therefore may be preferred.
Authors: Gabriel Alcoba; Carlos Ochoa; Sara Babo Martins; Rafael Ruiz de Castañeda; Isabelle Bolon; Franck Wanda; Eric Comte; Manish Subedi; Bhupendra Shah; Anup Ghimire; Etienne Gignoux; Francisco Luquero; Armand Seraphin Nkwescheu; Sanjib Kumar Sharma; François Chappuis; Nicolas Ray Journal: PLoS Negl Trop Dis Date: 2021-02-12
Authors: Katharina Auth; Sabine Bohnet; Cornelius Borck; Daniel Drömann; Klaas F Franzen Journal: Int J Environ Res Public Health Date: 2021-12-24 Impact factor: 3.390
Authors: Barbee I Whitaker; Mark Walderhaug; Susan Hinkins; Whitney R Steele; Brian Custer; Debra Kessler; German Leparc; Jerome L Gottschall; Walter Bialkowski; Susan L Stramer; Roger Y Dodd; Lauren Crowder; Farnaz Vahidnia; Beth H Shaz; Hany Kamel; Mark Rebosa; Michael Stern; Steven A Anderson Journal: Transfusion Date: 2020-08-03 Impact factor: 3.337