Evidence map›Paper›PMID 32646393›Full record

ArticleBMC public health2020

Impact of substandard and falsified antimalarials in Zambia: application of the SAFARI model.

Kathryn D Jackson, Colleen R Higgins, Sarah K Laing, Chiluba Mwila, Tamaki Kobayashi, Matthew M Ippolito, Sean Sylvia, Sachiko Ozawa

Open access · goldAbstract read
In one paragraph

Article in BMC public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
2.2field-weighted citation impact, top 12% of its field
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

10 citing papers in PubMed, 1 synthesis or guideline pooled it, 18 citations in OpenAlex.

  1. Pooled it
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  3. Review
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  5. Review
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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

8 authors at 4 institutions in 3 countries.

Kathryn D JacksonDepartment of Health Policy and Management, UNC Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA.
Colleen R HigginsDivision of Practice Advancement and Clinical Education, UNC Eshelman School of Pharmacy, University of North Carolina, CB#7574, Beard Hall, 115H, Chapel Hill, NC, 27599, USA.
Sarah K LaingDuke Global Health Institute, Duke University, Durham, NC, USA.
Chiluba MwilaDepartment of Pharmacy, School of Health Sciences, University of Zambia, Lusaka, Zambia.
Tamaki KobayashiDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Matthew M IppolitoMalaria Research Institute, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Sean SylviaDepartment of Health Policy and Management, UNC Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA.
Sachiko OzawaDivision of Practice Advancement and Clinical Education, UNC Eshelman School of Pharmacy, University of North Carolina, CB#7574, Beard Hall, 115H, Chapel Hill, NC, 27599, USA. ozawa@unc.edu.ORCID http://orcid.org/0000-0001-7608-9038
University of North Carolina at Chapel Hill · USJohns Hopkins University · USDuke University · USUniversity of Zambia · ZM

Funding

Clinical Pharmacology of Malaria Control and Elimination: Pharmacodynamics ofArtemisinin-based Combination Agents and their Barriers to Drug ResistanceK23AI139343 · NIAID · JOHNS HOPKINS UNIVERSITY · PI IPPOLITO, MATTHEW MICHAEL · 2020 to 2023
$773k
NIAID NIH HHS K23 AI139343
6 · The paper itself

Abstract

backgroundMany countries are striving to become malaria-free, but global reduction in case estimates has stagnated in recent years. Substandard and falsified medicines may contribute to this lack of progress. Zambia aims to eliminate their annual burden of 1.2 million pediatric malaria cases and 2500 child deaths due to malaria. We examined the health and economic impact of poor-quality antimalarials in Zambia.

methodsAn agent-based model, Substandard and Falsified Antimalarial Research Impact (SAFARI), was modified and applied to Zambia. The model was developed to simulate population characteristics, malaria incidence, patient care-seeking, disease progression, treatment outcomes, and associated costs of malaria for children under age five. Zambia-specific demographic, epidemiological, and cost inputs were extracted from the literature. Simulations were run to estimate the health and economic impact of poor-quality antimalarials, the effect of potential artemisinin resistance, and six additional malaria focused policy interventions.

resultsWe simulated annual malaria cases among Zambian children under five. At baseline, we found 2610 deaths resulting in $141.5 million in annual economic burden of malaria. We estimated that elimination of substandard and falsified antimalarials would result in an 8.1% (n = 213) reduction in under-five deaths, prevent 937 hospitalizations, and realize $8.5 million in economic savings, annually. Potential artemisinin resistance could further increase deaths by 6.3% (n = 166) and cost an additional $9.7 million every year.

conclusionsEliminating substandard and falsified antimalarials is an important step towards a malaria-free Zambia. Beyond the dissemination of insecticide-treated bed nets, indoor residual spraying, and other malaria control measures, attention must also be paid to assure the quality of antimalarial treatments.

Indexed as

AntimalarialsArtemisininsChildChild, PreschoolComputer SimulationCounterfeit DrugsHumansIncomeInfantMalariaModels, EconomicModels, TheoreticalPatient Acceptance of Health CareZambiaAntimalarialsartemisininArtemisininsCounterfeit DrugsAntimalarialsFalsifiedMalariaQualitySubstandardZambia

Identifiers

PMID32646393
PMCPMC7350731
OpenAlexW3042132004

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.