Stratified Sampling of Neighborhood Sections for Population Estimation: A Case Study of Bo City, Sierra Leone

Roger Hillson; Joel D Alejandre; Kathryn H Jacobsen; Rashid Ansumana; Alfred S Bockarie; Umaru Bangura; Joseph M Lamin; David A Stenger

doi:10.1371/journal.pone.0132850

Stratified Sampling of Neighborhood Sections for Population Estimation: A Case Study of Bo City, Sierra Leone

PLoS One. 2015 Jul 15;10(7):e0132850. doi: 10.1371/journal.pone.0132850. eCollection 2015.

Authors

Roger Hillson¹, Joel D Alejandre¹, Kathryn H Jacobsen², Rashid Ansumana³, Alfred S Bockarie³, Umaru Bangura⁴, Joseph M Lamin⁴, David A Stenger⁵

Affiliations

¹ Information Technology Division, Naval Research Laboratory, Washington, District of Columbia, United States of America.
² Department of Global and Community Health, George Mason University, Fairfax, Virginia, United States of America.
³ Njala University, Bo, Sierra Leone; Mercy Hospital Research Laboratory, Bo, Sierra Leone.
⁴ Mercy Hospital Research Laboratory, Bo, Sierra Leone.
⁵ Center for Bio/Molecular Science and Engineering, Naval Research Laboratory, Washington, District of Columbia, United States of America.

Abstract

There is a need for better estimators of population size in places that have undergone rapid growth and where collection of census data is difficult. We explored simulated estimates of urban population based on survey data from Bo, Sierra Leone, using two approaches: (1) stratified sampling from across 20 neighborhoods and (2) stratified single-stage cluster sampling of only four randomly-sampled neighborhoods. The stratification variables evaluated were (a) occupants per individual residence, (b) occupants per neighborhood, and (c) residential structures per neighborhood. For method (1), stratification variable (a) yielded the most accurate re-estimate of the current total population. Stratification variable (c), which can be estimated from aerial photography and zoning type verification, and variable (b), which could be ascertained by surveying a limited number of households, increased the accuracy of method (2). Small household-level surveys with appropriate sampling methods can yield reasonably accurate estimations of urban populations.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Cities*
Cluster Analysis
Computer Simulation
Humans
Population Density*
Residence Characteristics*
Sample Size
Sierra Leone
Surveys and Questionnaires
Uncertainty
Urban Population / statistics & numerical data*

Grants and funding

This work was funded by the Defense Threat Reduction Agency, Joint Science and Technology Office (http://www.dvidshub.net/unit/DTRA-CB#.UoUqZ9wo5zk) via contract to myself at the Naval Research Laboratory. A subcontract from NRL with George Mason University was used to provide support for contractors (Rashid Ansumana, Alfred Bockarie, Umaru Bangura and Joseph Lamin) working at Mercy Hospital Research Laboratory in Bo, Sierra Leone. There is no past, present or future Intellectual Property associated with the work described in the paper, and none of the authors have any financial interests or conflicts in the outcome of the study. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.