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Objective <p>Accurate and routine cause-of-death data are essential for health planning, yet many low- and middle-income countries lack comprehensive systems for such data, resulting in undocumented maternal and perinatal deaths. This article details the adaptation of the 2022 WHO Verbal Autopsy (VA) tool for maternal mortality surveillance in a linguistically diverse urban setting with high rates of out-of-facility deaths as part of the Lagos Verbal and Social Autopsy Sample Registration System project in Nigeria.</p> Results <p>The adaptation process enhanced the tool’s cultural sensitivity, language clarity, and system compatibility. Impersonal or potentially disrespectful terms (e.g., “the deceased”) were replaced, complex medical terms simplified (e.g., “abdominal pain” to “tummy pain”), and locally relevant options added for care providers and death locations. Context-specific skip patterns improved efficiency by focusing on maternal deaths and a rigorous translation process (forward/back translation in Yoruba and Pidgin English) ensured linguistic fidelity and local resonance. Validation included face and content review, role-play simulations, and pilot-testing with bereaved families. The adapted tool improved respondent comfort, data accuracy, and digital integration, incorporating global positioning system coordinates and interviewer identification numbers. The adapted tool retained compatibility with automated VA coding platforms and was incorporated into training regimen for data collectors.</p>

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Adapting the 2022 WHO verbal autopsy tool for use in Lagos State, Nigeria: insights from the LVASA-SRS project

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年12月29日

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  • Adeyemi Okunowo,
  • Uchenna Gwacham-Anisiobi,
  • Ndubuisi Ezumezu,
  • Hameed Adelabu,
  • Adedoyin Ogunyemi,
  • Teniola Lawanson,
  • Brenda Isikekpei,
  • Bosede B. Afolabi,
  • Aduragbemi Banke-Thomas

摘要

Objective

Accurate and routine cause-of-death data are essential for health planning, yet many low- and middle-income countries lack comprehensive systems for such data, resulting in undocumented maternal and perinatal deaths. This article details the adaptation of the 2022 WHO Verbal Autopsy (VA) tool for maternal mortality surveillance in a linguistically diverse urban setting with high rates of out-of-facility deaths as part of the Lagos Verbal and Social Autopsy Sample Registration System project in Nigeria.

Results

The adaptation process enhanced the tool’s cultural sensitivity, language clarity, and system compatibility. Impersonal or potentially disrespectful terms (e.g., “the deceased”) were replaced, complex medical terms simplified (e.g., “abdominal pain” to “tummy pain”), and locally relevant options added for care providers and death locations. Context-specific skip patterns improved efficiency by focusing on maternal deaths and a rigorous translation process (forward/back translation in Yoruba and Pidgin English) ensured linguistic fidelity and local resonance. Validation included face and content review, role-play simulations, and pilot-testing with bereaved families. The adapted tool improved respondent comfort, data accuracy, and digital integration, incorporating global positioning system coordinates and interviewer identification numbers. The adapted tool retained compatibility with automated VA coding platforms and was incorporated into training regimen for data collectors.