Evidence map›Paper›PMID 30485720›Full record

ArticleJournal of the International AIDS Society2018

The importance of local epidemic conditions in monitoring progress towards HIV epidemic control in Kenya: a modelling study.

Sarah-Jane Anderson, Geoffrey P Garnett, Joanne Enstone, Timothy B Hallett

Abstract read
In one paragraph

Article in Journal of the International AIDS Society, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–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

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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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

4 authors.

Sarah-Jane AndersonDepartment of Infectious Disease Epidemiology, Imperial College London, London, UK.ORCID 0000-0002-5945-2285
Geoffrey P GarnettThe Bill and Melinda Gates Foundation, Seattle, WA, USA.
Joanne EnstoneDivision of Public Health and Epidemiology, The University of Nottingham, Nottingham, UK.
Timothy B HallettDepartment of Infectious Disease Epidemiology, Imperial College London, London, UK.

Funding

Medical Research Council MR/R015600/1
6 · The paper itself

Abstract

introductionSetting and monitoring progress towards targets for HIV control is critical in ensuring responsive programmes. Here, we explore how to apply targets for reduction in HIV incidence to local settings and which indicators give the strongest signal of a change in incidence in the population and are therefore most important to monitor.

methodsWe use location-specific HIV transmission models, tailored to the epidemics in the counties and major cities in Kenya, to project a wide range of plausible future epidemic trajectories through varying behaviours, treatment coverage and prevention interventions. We look at the change in incidence across modelled scenarios in each location between 2015 and 2030 to inform local target setting. We also simulate the measurement of a library of potential indicators and assess which are most strongly associated with a change in incidence.

resultsConsiderable variation was observed in the trajectory of the local epidemics under the plausible scenarios defined (only 10 of 48 locations saw a median reduction in incidence of greater than or equal to an 80% target by 2030). Indicators that provide strong signals in certain epidemic types may not perform consistently well in settings with different epidemiological features. Predicting changes in incidence is more challenging in advanced generalized epidemics compared to concentrated epidemics where changes in high-risk sub-populations track more closely to the population as a whole. Many indicators demonstrate only limited association with incidence (such as "condom use" or "pre-exposure prophylaxis coverage"). This is because many other factors (low effectiveness, impact of other interventions, countervailing changes in risk behaviours, etc.) can confound the relationship between interventions and their ultimate long-term impact, especially for an intervention with low expected coverage. The population prevalence of viral suppression shows the most consistent associations with long-term changes in incidence even in the largest generalized epidemics.

conclusionsTarget setting should be appropriate for the local epidemic and what can feasibly be achieved. There is no one universally reliable indicator to predict future HIV incidence across settings. Thus, the signature of epidemic control must contain indications of success across a wide range of interventions and outcomes.

Indexed as

Population SurveillanceAdultEpidemicsFemaleHIVHIV InfectionsHumansIncidenceKenyaMaleModels, BiologicalPre-Exposure ProphylaxisPrevalenceRisk FactorsepidemiologyforecastingHIV Infectionsmodelspopulation surveillanceprogramme evaluationtheoretical

Identifiers

PMID30485720
PMCPMC6260921

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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.