Inferring antenatal care visit timing in low- and middle-income countries: Methods to inform potential maternal vaccine coverage

PLoS One. 2020 Aug 20;15(8):e0237718. doi: 10.1371/journal.pone.0237718. eCollection 2020.

Abstract

Background: The timing of antenatal care (ANC) visits directly affect health intervention coverage and impact, especially for those interventions requiring strict gestational age windows for administration, such as maternal respiratory syncytial virus (RSV) vaccine. Existing nationally representative population-based surveys do not record the timing of ANC visits beyond the first, limiting the availability of reliable data around timing of subsequent ANC visits in most low- and middle-income countries (LMICs). Here, we describe a model that estimates the timing of ANC visits by gestational age using publicly available multi-country survey data.

Methods and findings: We used the Demographic and Health Surveys (DHS) data from 69 LMICs. We used several factors to estimate the timing of subsequent ANC visits by gestation age: the timing of the first ANC visit (ANC1) in a given pregnancy, derived from the DHS; the country's reported average ANC coverage at each ANC visit (ANC1 through the fourth ANC visit [ANC4]); and the World Health Organization's guidance on recommended ANC visit. We then used the timing of ANC visit by gestation age to predict the coverage of a potential maternal RSV vaccine administered at 24-36 weeks of gestation. We calculated the maternal immunization coverage by summing the number of eligible women vaccinated at any ANC visit divided by the total number of pregnant women. We find, in general, countries with higher ANC1 coverage were predicted to have higher vaccination coverage. In 82% of countries, the modeled vaccine coverage is less than ANC4 coverage.

Conclusions: The methods illustrated in this paper have implications on the precision of estimating impact and programmatic feasibility of time-critical interventions, especially for pregnant women. The methods can be easily adapted to vaccine demand forecasts models, vaccine impact assessments, and cost-effectiveness analyses and can be adapted to other maternal interventions that have administration timing restrictions.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Developing Countries / economics
  • Female
  • Gestational Age*
  • Health Surveys
  • Humans
  • Poverty / economics
  • Pregnancy
  • Prenatal Care / economics
  • Prenatal Care / methods*
  • Respiratory Syncytial Virus Infections / economics
  • Respiratory Syncytial Virus Infections / epidemiology
  • Respiratory Syncytial Virus Infections / pathology
  • Respiratory Syncytial Virus Infections / prevention & control*
  • Respiratory Syncytial Viruses / pathogenicity
  • Viral Vaccines / administration & dosage*
  • Viral Vaccines / economics

Substances

  • Viral Vaccines

Grants and funding

This work was supported by a grant (#OPP1088264) from the Bill & Melinda Gates Foundation, Seattle, WA. The findings and conclusions contained within are those of the authors and do not necessarily reflect positions or policies of the Bill & Melinda Gates Foundation.