Back to Search Start Over

Using paired serology and surveillance data to quantify dengue transmission and control during a large outbreak in Fiji

Authors :
Colleen L. Lau
Jean-Claude Manuguerra
Sebastian Funk
Stéphane Hué
John Edmunds
Martin L. Hibberd
Mike Kama
Jessica Vanhomwegen
Alasdair D Henderson
Van-Mai Cao-Lormeau
Conall H. Watson
John Aaskov
Maite Aubry
Oliver J. Brady
Adam J. Kucharski
Eric J. Nilles
London School of Hygiene and Tropical Medicine (LSHTM)
Fiji Centre for Communicable Disease Control [Suva, Fidji]
University of the South Pacific (USP)
Institut Louis Malardé [Papeete] (ILM)
Institut de Recherche pour le Développement (IRD)
Institut Pasteur [Paris] (IP)
Australian National University (ANU)
Queensland University of Technology [Brisbane] (QUT)
World Health Organization Division of Pacific Technical Support
Pôle de recherche et de veille sur les maladies infectieuses émergentes
Institut de Recherche pour le Développement (IRD)-Institut de Recherche pour le Développement (IRD)
206250/Z/17/Z/Wellcome Trust/United Kingdom
MR/J003999/1/Medical Research Council/United Kingdom
Pacific Funds N°03016-20/05/16/French Ministry for Europe and Foreign Affairs/International
1109035/National Health and Medical Research Council/International
ANR-10-LABX-62-IBEID/Commissariat Général à l'Investissement/International
ANR-10-LABX-0062,IBEID,Integrative Biology of Emerging Infectious Diseases(2010)
Institut Pasteur [Paris]
Source :
eLife, Vol 7 (2018), eLife, eLife, 2018, 7, pp.e34848. ⟨10.7554/elife.34848⟩, eLife, eLife Sciences Publication, 2018, 7, pp.e34848. ⟨10.7554/elife.34848⟩
Publication Year :
2019
Publisher :
eLife Sciences Publications, 2019.

Abstract

Dengue is a major health burden, but it can be challenging to examine transmission and evaluate control measures because outbreaks depend on multiple factors, including human population structure, prior immunity and climate. We combined population-representative paired sera collected before and after the 2013/14 dengue-3 outbreak in Fiji with surveillance data to determine how such factors influence transmission and control in island settings. Our results suggested the 10–19 year-old age group had the highest risk of infection, but we did not find strong evidence that other demographic or environmental risk factors were linked to seroconversion. A mathematical model jointly fitted to surveillance and serological data suggested that herd immunity and seasonally varying transmission could not explain observed dynamics. However, the model showed evidence of an additional reduction in transmission coinciding with a vector clean-up campaign, which may have contributed to the decline in cases in the later stages of the outbreak.<br />eLife digest Dengue fever – a disease spread by mosquitos – causes large outbreaks in Asia and the South Pacific islands. Health agencies often try to reduce the spread of the disease by removing mosquito breeding grounds, like old tires and containers that may hold standing water. But it can be difficult to tell whether these preventive measures work because dengue transmission depends on many factors, including the weather and how many people had developed immunity because of previous infections. A common way to study patterns of infection and immunity is to collect blood samples from a subset of the population before and after an outbreak. Unfortunately, large dengue outbreaks occur sporadically on islands, making it hard to set up a study like this ahead of an outbreak. During 2013 and 2014, there was a major dengue outbreak in Fiji, with over 25,000 suspected cases reported. In response, the government introduced a nationwide mosquito clean-up campaign. As luck would have it, a group of researchers had collected blood samples immediately before the outbreak for an unrelated study of typhoid fever and leptospirosis. Now, Kucharski et al. – who include the researchers who collected those pre-outbreak blood samples – show that the clean-up campaign coincided with a reduction in transmission of the disease. Participants whose blood was collected before the dengue outbreak were invited to provide another blood sample after the dengue outbreak. This allowed Kucharski et al. to identify individuals who had already developed immunity to dengue before the outbreak and those who were likely infected during the outbreak. Comparing blood samples taken before and after the outbreak revealed that children and teenagers between the ages of 10 and 19 had the greatest risk of infection during the outbreak. No other demographic or environmental factors were strongly linked to the likelihood of infection. Computer models using the data also showed that the clean-up efforts could explain the reduced dengue transmission during the outbreak. These findings suggest that studying immunity against dengue can lead to a better understanding of disease transmission. This may help health agencies to gauge the effects of efforts to control this disease, and possibly forecast future outbreaks.

Details

Language :
English
ISSN :
2050084X
Database :
OpenAIRE
Journal :
eLife, Vol 7 (2018), eLife, eLife, 2018, 7, pp.e34848. ⟨10.7554/elife.34848⟩, eLife, eLife Sciences Publication, 2018, 7, pp.e34848. ⟨10.7554/elife.34848⟩
Accession number :
edsair.doi.dedup.....7fade489b05be2d89fe6c29bb74b19d4
Full Text :
https://doi.org/10.7554/elife.34848