Evidence map›Paper›PMID 40469402›Full record

ReviewJournal of public health in Africa2025

What are our options for mortality data collection and how can they provide HIV-specific information?

Carlie L Sulpizio, Zaena Tessema, Diane Morof, Andrew Boyd, Elfriede Agyemang, Martha Knuth, Danielle Fernandez, Monita Patel, Hammad Ali

Abstract readReview
In one paragraph

Review in Journal of public health in Africa, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Carlie L SulpizioDivision of Global HIV and Tuberculosis, United States (US) Centers for Disease Control and Prevention, Atlanta, GA, United States of America.ORCID https://orcid.org/0000-0001-5623-8745
Zaena TessemaDivision of Global HIV and Tuberculosis, United States (US) Centers for Disease Control and Prevention, Atlanta, GA, United States of America.ORCID https://orcid.org/0009-0007-8386-5761
Diane MorofDivision of Global HIV and Tuberculosis, United States (US) Centers for Disease Control and Prevention, Atlanta, GA, United States of America.ORCID https://orcid.org/0000-0003-1299-5204
Andrew BoydDivision of Global HIV and Tuberculosis, United States (US) Centers for Disease Control and Prevention, Atlanta, GA, United States of America.ORCID https://orcid.org/0000-0001-6354-6818
Elfriede AgyemangDivision of Global HIV and Tuberculosis, United States (US) Centers for Disease Control and Prevention, Atlanta, GA, United States of America.ORCID https://orcid.org/0000-0002-7865-5950
Martha KnuthDivision of Global HIV and Tuberculosis, United States (US) Centers for Disease Control and Prevention, Atlanta, GA, United States of America.ORCID https://orcid.org/0000-0003-4264-1642
Danielle FernandezDivision of Global HIV and Tuberculosis, United States (US) Centers for Disease Control and Prevention, Atlanta, GA, United States of America.ORCID https://orcid.org/0000-0003-3717-236X
Monita PatelDivision of Global HIV and Tuberculosis, United States (US) Centers for Disease Control and Prevention, Atlanta, GA, United States of America.ORCID https://orcid.org/0000-0003-4840-1914
Hammad AliDivision of Global HIV and Tuberculosis, United States (US) Centers for Disease Control and Prevention, Atlanta, GA, United States of America.ORCID https://orcid.org/0000-0001-7722-2486

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Mortality data are critical for understanding changes in population health, detecting and monitoring diseases, guiding public health responses and evaluating interventions like human immunodeficiency viruses (HIV) prevention and treatment programmes. However, in low- and middle-income countries (LMICs), comprehensive mortality data are often hindered by a high incidence of deaths occurring outside healthcare facilities and the lack of robust data systems, creating a significant knowledge gap. Aim: This article presents methodologies for collecting mortality data, particularly in LMICs, to provide accurate and reliable information on overall and cause-specific mortality, including HIV-related deaths. Setting: This study explore methods that may be useful in LMICs, where mortality data systems are often ad-hoc, sub-national and incomplete. Method: Available methods were examined for collecting mortality data and report on the strengths, weaknesses and resource considerations for each method. Results: The analysis shows that while Civil Registration and Vital Statistics is the gold standard for mortality data collection, its implementation is challenging because of differing priorities of stakeholders, infrastructural and legal barriers. Alternative methods may provide valuable data but may have limitations in coverage and resource allocation. Integrating these methods can enhance understanding of mortality data, including for HIV-related deaths. Conclusion: Implementing a combination of mortality data-collection methods could address gaps in mortality data in LMICs. Tailoring interventions based on these data may improve health outcomes and support HIV epidemic control efforts. Contribution: This study could be used as a resource to ministries of health, national and international public health organisations, researchers and funding bodies as it can assist countries in selecting the mortality surveillance strategy that best fits their HIV epidemic, and available infrastructure and financial resources.

Indexed as

civil Registrationdata collectionHIV/AIDSmortalitysurveillancevital statistics

Identifiers

PMID40469402
PMCPMC12135155

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.