Evidence map›Paper›PMID 29132357›Full record

ReviewMalaria journal2017

Mapping multiple components of malaria risk for improved targeting of elimination interventions.

Justin M Cohen, Arnaud Le Menach, Emilie Pothin, Thomas P Eisele, Peter W Gething, Philip A Eckhoff, Bruno Moonen, Allan Schapira, David L Smith

Open access · goldAbstract readReview
In one paragraph

Review in Malaria journal, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.

0numbers the graph read from it
0cells of the map it votes in
41citing papers in PubMed
9.2field-weighted citation impact, top 2% 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

41 citing papers in PubMed, 78 citations in OpenAlex.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. Review
  15. Article
  16. IdentifyingeLife · 2021
    Article
  17. Article
  18. Article
  19. Article
  20. Review
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 at 8 institutions in 4 countries.

Justin M CohenClinton Health Access Initiative, 383 Dorchester Ave., Suite 400, Boston, MA, 02127, USA. jcohen@clintonhealthaccess.org.
Arnaud Le MenachClinton Health Access Initiative, 383 Dorchester Ave., Suite 400, Boston, MA, 02127, USA.
Emilie PothinSwiss Tropical and Public Health Institute, Socinstrasse 57, 4051, Basel, Switzerland.
Thomas P EiseleCenter for Applied Malaria Research and Evaluation, Tulane University School of Public Health and Tropical Medicine, 1440 Canal St (2300), New Orleans, LA, 70112, USA.
Peter W GethingOxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, OX3 7LF, UK.
Philip A EckhoffInstitute for Disease Modeling, Building IV, 3150 139th Ave SE, Bellevue, WA, 98005, USA.
Bruno MoonenBill & Melinda Gates Foundation, PO Box 23350, Seattle, WA, 98102, USA.
Allan SchapiraIndependent Consultant, Legazpi City, Philippines.
David L SmithInstitute for Health Metrics and Evaluation, University of Washington, 2301 Fifth Ave., Suite 600, Seattle, WA, 98121, USA.
Clinton Health Access Initiative · USBellevue Hospital Center · USBill & Melinda Gates Foundation · USSwiss Tropical and Public Health Institute · CHTulane University · USUniversity of Oxford · GBUniversity of Santo Tomas–Legazpi · PHUniversity of Washington · US

Funding

Gates Foundation OPP1034348Medical Research Council MR/K00669X/1
6 · The paper itself

Abstract

There is a long history of considering the constituent components of malaria risk and the malaria transmission cycle via the use of mathematical models, yet strategic planning in endemic countries tends not to take full advantage of available disease intelligence to tailor interventions. National malaria programmes typically make operational decisions about where to implement vector control and surveillance activities based upon simple categorizations of annual parasite incidence. With technological advances, an enormous opportunity exists to better target specific malaria interventions to the places where they will have greatest impact by mapping and evaluating metrics related to a variety of risk components, each of which describes a different facet of the transmission cycle. Here, these components and their implications for operational decision-making are reviewed. For each component, related mappable malaria metrics are also described which may be measured and evaluated by malaria programmes seeking to better understand the determinants of malaria risk. Implementing tailored programmes based on knowledge of the heterogeneous distribution of the drivers of malaria transmission rather than only consideration of traditional metrics such as case incidence has the potential to result in substantial improvements in decision-making. As programmes improve their ability to prioritize their available tools to the places where evidence suggests they will be most effective, elimination aspirations may become increasingly feasible.

Indexed as

Decision MakingNational Health ProgramsCommunicable Disease ControlMalariaRiskEpidemiologyHealth policyMalariaOperational planningRisk mapping

Identifiers

PMID29132357
PMCPMC5683539
OpenAlexW2769690433

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.