Evidence map›Paper›PMID 33075052›Full record

ArticlePLoS computational biology2020

After the honeymoon, the divorce: Unexpected outcomes of disease control measures against endemic infections.

Brandon Hollingsworth, Kenichi W Okamoto, Alun L Lloyd

Open access · goldAbstract read
In one paragraph

Article in PLoS computational biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.8field-weighted citation impact, top 13% 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, 19 citations in OpenAlex.

  1. Article
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  8. Increases in group A streptococcal infections in the pediatric population in Houston, TX, 2022.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2023
    Article
  9. Article
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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

3 authors at 2 institutions in 1 country.

Brandon HollingsworthBiomathematics Graduate Program, North Carolina State University, Raleigh, NC, United States of America.ORCID 0000-0002-1772-8191
Kenichi W OkamotoDepartment of Biology, University of St. Thomas, St. Paul, MN, United States of America.ORCID 0000-0002-1889-4538
Alun L LloydBiomathematics Graduate Program, North Carolina State University, Raleigh, NC, United States of America.ORCID 0000-0002-6389-6321
North Carolina State University · USUniversity of St. Thomas - Minnesota · US

Funding

Surveillance Core (B)P01AI098670 · NIAID · UNIVERSITY OF CALIFORNIA AT DAVIS · PI MORRISON, AMY CELESTE · 2014 to 2018
$7.9M
Combining Aedes aegypti genomics and modeling to improve gene drive strategies and our understanding of resistance evolutionR01AI139085 · NIAID · NORTH CAROLINA STATE UNIVERSITY RALEIGH · PI GOULD, FRED · 2018 to 2022
$1.9M
Improving Robustness of a Tactical Model of Aedes/Dengue DynamicsR01AI091980 · NIAID · NORTH CAROLINA STATE UNIVERSITY RALEIGH · PI GOULD, FRED · 2011 to 2014
$1.3M
NIAID NIH HHS P01 AI098670NIAID NIH HHS R01 AI091980NIAID NIH HHS R01 AI139085
6 · The paper itself

Abstract

The lack of effective vaccines for many endemic diseases often forces policymakers to rely on non-immunizing control measures, such as vector control, to reduce the massive burden of these diseases. Controls can have well-known counterintuitive effects on endemic infections, including the honeymoon effect, in which partially effective controls cause not only a greater initial reduction in infection than expected, but also large outbreaks during control resulting from accumulation of susceptibles. Unfortunately, many control measures cannot be maintained indefinitely, and the results of cessation are poorly understood. Here, we examine the results of stopped or failed non-immunizing control measures in endemic settings. By using a mathematical model to compare the cumulative number of cases expected with and without control, we show that deployment of control can lead to a larger total number of infections, counting from the time that control started, than without any control-the divorce effect. This result is directly related to the population-level loss of immunity resulting from non-immunizing controls and is seen in a variety of models when non-immunizing controls are used against an infection that confers immunity. Finally, we examine three control plans for minimizing the magnitude of the divorce effect in seasonal infections and show that they are incapable of eliminating the divorce effect. While we do not suggest stopping control programs that rely on non-immunizing controls, our results strongly argue that the accumulation of susceptibility should be considered before deploying such controls against endemic infections when indefinite use of the control is unlikely. We highlight that our results are particularly germane to endemic mosquito-borne infections, such as dengue virus, both for routine management involving vector control and for field trials of novel control approaches, and in the context of non-pharmaceutical interventions aimed at COVID-19.

Indexed as

Immunization ProgramsAnimalsBasic Reproduction NumberCommunicable Disease ControlCoronavirus InfectionsCOVID-19COVID-19 VaccinesCulicidaeDengue VaccinesEndemic DiseasesHealth PolicyHumansInsect VectorsModels, TheoreticalPandemicsPneumonia, ViralCOVID-19 VaccinesDengue VaccinesRubella VaccineViral Vaccines

Identifiers

PMID33075052
PMCPMC7595641
OpenAlexW3093280101

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.