Population Enumeration and Household Utilization Survey Methods in the Enterics for Global Health (EFGH): Shigella Surveillance Study

Abstract

Background: Accurate estimation of diarrhea incidence from facility-based surveillance requires estimating the population at risk and accounting for case patients who do not seek care. The Enterics for Global Health (EFGH) Shigella surveillance study will characterize population denominators and healthcare-seeking behavior proportions to calculate incidence rates of Shigella diarrhea in children aged 6-35 months across 7 sites in Africa, Asia, and Latin America.

Methods: The Enterics for Global Health (EFGH) Shigella surveillance study will use a hybrid surveillance design, supplementing facility-based surveillance with population-based surveys to estimate population size and the proportion of children with diarrhea brought for care at EFGH health facilities. Continuous data collection over a 24 month period captures seasonality and ensures representative sampling of the population at risk during the period of facility-based enrollments. Study catchment areas are broken into randomized clusters, each sized to be feasibly enumerated by individual field teams.

Conclusions: The methods presented herein aim to minimize the challenges associated with hybrid surveillance, such as poor parity between survey area coverage and facility coverage, population fluctuations, seasonal variability, and adjustments to care-seeking behavior.

Keywords: EFGH; Shigella; healthcare utilization survey; hybrid surveillance design; population enumeration.

Figure 1.

The process of creating and ordering clusters and assigning the cluster identification (ID) number within each Enterics for Global Health (EFGH) study area. Top left, EFGH-Pakistan study area borders (bold line). Top center, Square grid matching the dimensions of the Pakistan WorldPop raster (grid of fine lines), bounded by the EFGH-Pakistan study area (bold line). Top right, Detailed map of the northwest section of the Pakistan study area, with square grid (grid of fine lines) bounded by the EFGH-Pakistan study area (bold line). Bottom left, Each cluster is randomly numbered and labeled with a cluster ID number. Field teams visit each cluster in sequential order starting with cluster 1. Borders of the EFGH-Pakistan study area are bounded in blue. Bottom right, Detailed view of cluster 1 and surrounding clusters. The EFGH-Pakistan study site is bounded in blue. Cluster 711 is truncated by the study area. The Pakistan study area extends into the water in places owing to the delineation of official Union Council boundaries and the possibility of people living directly on the shoreline.

Figure 2.

Using WorldPop to inform the size and estimated population within each cluster. Left, Square grid overlaid on the WorldPop raster in the Enterics for Global Health––Kenya study site. In this example, the average grid square has an estimated population of approximately 3.5 persons. Right, A total of 144 grid squares (fine blue lines) were combined to reach an average estimated population of 500 people per cluster (bold red lines). It was determined that clusters should be composed of 12 grid squares by 12 grid squares after iteratively calculating the optimum size using the equation, (500/p) × No. of input cells, where p is the mean population of input cells (which can be WorldPop grid squares or clusters from a prior iteration of the calculation). To ensure that clusters have a square aspect ratio, we took the square root of the number of required input cells and rounded it to the nearest whole number.

Figure 3.

Subclusters (clusters 10, 170, 192, 500, and 549) in the Enterics for Global Health–Kenya study site, divided into quadrants based on estimated population size. Subclusters are shaded. Clusters along the boundary of the catchment area (thicker boundary line) are truncated; clusters 157 and 175 are examples of truncated clusters.