# Conducting nationwide cohort COVID-19 serology surveys on a nation with limited resources and decentralized governance: Evidence from Indonesia

## TL;DR

This paper describes how Indonesia conducted nationwide COVID-19 serology surveys despite limited resources and decentralized governance.

## Contribution

The study provides practical lessons and methods for conducting large-scale serology surveys in resource-limited, geographically diverse countries.

## Key findings

- Cross-sectoral collaboration enabled efficient sampling using civil registration databases.
- Involving experienced phlebotomists reduced preparation time for sample collection.
- Probability-proportional-to-size sampling ensured representation of non-urban areas.

## Abstract

Knowing the level of SARS-CoV-2 transmission is crucial for decision-making on Coronavirus disease (COVID-19) handling. Guidelines for measuring SARS-CoV-2 antibodies to estimate seroprevalence are conceptually straightforward and internationally available. However, challenges exist for developing countries with limited laboratory capacity, diverse geographical topography, fragmented health information systems and limited resources such as Indonesia. One year after the first case was confirmed in Indonesia, approximately ten infections were undiagnosed or underreported for every reported case. Under those circumstances, we described the method and lessons learned in conducting nationwide cohort COVID-19 serology surveys in a nation with limited resources, such as Indonesia. •Strong cross-sectoral collaboration between ministries and levels of governance (central and subnational) enables strategic use of civil registration database for efficient sampling.•All agglomeration districts (highly dense population and urban area) were selected as study sites, and additional non-agglomeration districts were selected using probability-proportional-to-size (PPS).•Involving the experienced phlebotomist in community health service provider and district laboratory cut down preparation time.

Strong cross-sectoral collaboration between ministries and levels of governance (central and subnational) enables strategic use of civil registration database for efficient sampling.

All agglomeration districts (highly dense population and urban area) were selected as study sites, and additional non-agglomeration districts were selected using probability-proportional-to-size (PPS).

Involving the experienced phlebotomist in community health service provider and district laboratory cut down preparation time.

PHO = Provincial Health Office | DHO = District Health Office | Govt lab = Government laboratory, FKM UI = Fakultas Kesehatan Masyarakat (Faculty of Public Health) Universitas IndonesiaImage, graphical abstract