Serology describes a profile of declining malaria transmission in Farafenni, The Gambia

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Abstract

Background

Malaria morbidity and mortality has declined in recent years in a number of settings. The ability to describe changes in malaria transmission associated with these declines is important in terms of assessing the potential effects of control interventions, and for monitoring and evaluation purposes.

Methods

Data from five cross-sectional surveys conducted in Farafenni and surrounding villages on the north bank of River Gambia between 1988 and 2011 were compiled. Antibody responses to MSP-1 ₁₉ were measured in samples from all surveys, data were normalized and expressed as seroprevalence and seroconversion rates (SCR) using different mathematical models.

Results

Results showed declines in serological metrics with seroprevalence in children aged one to 5 years dropping from 19 % (95 % CI 15–23 %) in 1988 to 1 % (0–2 %) in 2011 ( p value for trend in proportions < 0.001) and the SCR dropping from 0.069 year ⁻¹ (0.059–0.080) to 0.022 year ⁻¹ (0.017–0.028; p = 0.004). The serological data were consistent with previously described drops in both parasite prevalence in children aged 1–5 years (62 %, 57–66 %, in 1988 to 2 %, 0–4 %, in 2011; p < 0.001), and all-cause under five mortality rates (37 per 1000 person-years, 34–41, in 1990 to 17, 15–19, in 2006; p = 0.059).

Conclusions

This analysis shows accurate reconstruction of historical malaria transmission patterns in the Farafenni area using anti-malarial antibody responses. Demonstrating congruence between serological measures, and conventional clinical and parasitological measures suggests broader utility for serology in monitoring and evaluation of malaria transmission.

Electronic supplementary material

The online version of this article (doi:10.1186/s12936-015-0939-1) contains supplementary material, which is available to authorized users.

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Most cited references 27

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Serology: a robust indicator of malaria transmission intensity?

Patrick Corran, Paul A. Coleman, Eleanor M. Riley … (2007)

To estimate the burden of malarial disease, and evaluate the likely effects of control strategies, requires reliable predictions of malaria transmission intensity. It has long been suggested that antimalarial antibody prevalences could provide a more accurate estimate of transmission intensity than traditional measures such as parasite prevalence or entomological inoculation rates, but there has been no systematic evaluation of this approach. Now, the availability of well characterized malarial antigens allows us to test whether serological measurements provide a practical method for estimating transmission. Here we present a suggested methodology, highlight the advantages and shortcomings of serological measurements of malaria transmission and identify areas in which further work is desirable.

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Effect of two different house screening interventions on exposure to malaria vectors and on anaemia in children in The Gambia: a randomised controlled trial.

P Snell, Clare Green, David Ameh … (2009)

House screening should protect people against malaria. We assessed whether two types of house screening--full screening of windows, doors, and closing eaves, or installation of screened ceilings--could reduce house entry of malaria vectors and frequency of anaemia in children in an area of seasonal malaria transmission. During 2006 and 2007, 500 occupied houses in and near Farafenni town in The Gambia, an area with low use of insecticide-treated bednets, were randomly assigned to receive full screening, screened ceilings, or no screening (control). Randomisation was done by computer-generated list, in permuted blocks of five houses in the ratio 2:2:1. Screening was not treated with insecticide. Exposure to mosquitoes indoors was assessed by fortnightly light trap collections during the transmission season. Primary endpoints included the number of female Anopheles gambiae sensu lato mosquitoes collected per trap per night. Secondary endpoints included frequency of anaemia (haemoglobin concentration <80 g/L) and parasitaemia at the end of the transmission season in children (aged 6 months to 10 years) who were living in the study houses. Analysis was by modified intention to treat (ITT), including all randomised houses for which there were some outcome data and all children from those houses who were sampled for haemoglobin and parasitaemia. This study is registered as an International Standard Randomised Controlled Trial, number ISRCTN51184253. 462 houses were included in the modified ITT analysis (full screening, n=188; screened ceilings, n=178; control, n=96). The mean number of A gambiae caught in houses without screening was 37.5 per trap per night (95% CI 31.6-43.3), compared with 15.2 (12.9-17.4) in houses with full screening (ratio of means 0.41, 95% CI 0.31-0.54; p<0.0001) and 19.1 (16.1-22.1) in houses with screened ceilings (ratio 0.53, 0.40-0.70; p<0.0001). 755 children completed the study, of whom 731 had complete clinical and covariate data and were used in the analysis of clinical outcomes. 30 (19%) of 158 children from control houses had anaemia, compared with 38 (12%) of 309 from houses with full screening (adjusted odds ratio [OR] 0.53, 95% CI 0.29-0.97; p=0.04), and 31 (12%) of 264 from houses with screened ceilings (OR 0.51, 0.27-0.96; p=0.04). Frequency of parasitaemia did not differ between intervention and control groups. House screening substantially reduced the number of mosquitoes inside houses and could contribute to prevention of anaemia in children. Medical Research Council.

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Estimating the annual entomological inoculation rate for Plasmodium falciparum transmitted by Anopheles gambiae s.l. using three sampling methods in three sites in Uganda

Maxwell Kilama, David L Smith, Robert Hutchinson … (2014)

Background The Plasmodium falciparum entomological inoculation rate (PfEIR) is a measure of exposure to infectious mosquitoes. It is usually interpreted as the number of P. falciparum infective bites received by an individual during a season or annually (aPfEIR). In an area of perennial transmission, the accuracy, precision and seasonal distribution (i.e., month by month) of aPfEIR were investigated. Data were drawn from three sites in Uganda with differing levels of transmission where falciparum malaria is transmitted mainly by Anopheles gambiae s.l. Estimates of aPfEIR derived from human-landing catches – the classic method for estimating biting rates – were compared with data from CDC light traps, and with catches of knock down and exit traps separately and combined. Methods Entomological surveillance was carried out over one year in 2011/12 in three settings: Jinja, a peri-urban area with low transmission; Kanungu, a rural area with moderate transmission; and Nagongera, Tororo District, a rural area with exceptionally high malaria transmission. Three sampling approaches were used from randomly selected houses with collections occurring once a month: human-landing collections (eight houses), CDC light traps (100 houses) and paired knock-down and exit traps each month (ten houses) for each setting. Up to 50 mosquitoes per month from each household were tested for sporozoites with P. falciparum by ELISA. Human biting rate (HBR) data were estimated month by month. P. falciparum Sporozoite rate (PfSR) for yearly and monthly data and confidence intervals were estimated using the binomial exact test. Monthly and yearly estimates of the HBR, the PfSR, and the PfEIR were estimated and compared. Results The estimated aPfEIR values using human-landing catch data were 3.8 (95% Confidence Intervals, CI 0-11.4) for Jinja, 26.6 (95% CI 7.6-49.4) for Kanungu, and 125 (95% CI 72.2-183.0) for Tororo. In general, the monthly PfEIR values showed strong seasonal signals with two peaks from May-June and October-December, although the precise timing of the peaks differed between sites. Estimated HBRs using human-landing catches were strongly correlated with those made using CDC light traps (r2 = 0.67, p < 0.001), and with either knock-down catches (r2 = 0.56, p < 0.001) and exit traps (r2 = 0.82, p < 0.001) or the combined catches (r2 = 0.73, p < 0.001). Using CDC light trap catch data, the PfSR in Tororo was strongly negatively correlated with monthly HBR (r2 = 0.44, p = 0.01). In other sites, no patterns in the PfSR were discernible because either the number P. falciparum of sporozoite positive mosquitoes or the total number of mosquitoes caught was too low. Conclusions In these settings, light traps provide an alternative method for sampling indoor-resting mosquitoes to human-landing catches and have the advantage that they protect individuals from being bitten during collection, are easy to use and are not subject to collector bias. Knock-down catches and exit traps could also be used to replace human-landing catches. Although these are cheaper, they are subject to collector bias.

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Author and article information

Contributors

Lotus L. van den Hoogen: lotus.vandenhoogen@lshtm.ac.uk

Jamie T. Griffin: jamie.griffin@imperial.ac.uk

Jackie Cook: jackie.cook@lshtm.ac.uk

Nuno Sepúlveda: nuno.sepulveda@lshtm.ac.uk

Patrick Corran: patrick.corran@lshtm.ac.uk

David J. Conway: david.conway@lsthm.ac.uk

Paul Milligan: paul.milligan@lshtm.ac.uk

Muna Affara: maffara@mrc.gm

Stephen J. Allen: stephen.allen@lstmed.ac.uk

Carla Proietti: carla.proietti@qimrberghofer.edu.au

Serign J. Ceesay: sjceesay@mrc.gm

Geoffrey A. Targett: geoff.targett@lshtm.ac.uk

Umberto D’Alessandro: umberto.dalessandro@lshtm.ac.uk

Brian Greenwood: brian.greenwood@lshtm.ac.uk

Eleanor M. Riley: eleanor.riley@lshtm.ac.uk

Chris Drakeley: chris.drakeley@lshtm.ac.uk

Journal

Journal ID (nlm-ta): Malar J

Journal ID (iso-abbrev): Malar. J

Title: Malaria Journal

Publisher: BioMed Central (London )

ISSN (Electronic): 1475-2875

Publication date (Electronic): 22 October 2015

Publication date PMC-release: 22 October 2015

Publication date Collection: 2015

Volume: 14

Electronic Location Identifier: 416

Affiliations

[ ]Department of Immunology and Infection, Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT UK

[ ]MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Faculty of Medicine, Imperial College London, London, W2 1PG UK

[ ]Centre of Statistics and Applications of University of Lisbon, Faculdade de Ciências Da Universidade de Lisboa, Bloco C6—Piso 4, 1749-1016 Lisbon, Portugal

[ ]Disease Control and Elimination, Medical Research Council Unit, Fajara, 220 The Gambia

[ ]Department of Clinical Sciences, Liverpool School of Tropical Medicine, Liverpool, L3 5QA UK

[ ]Infectious Diseases Programme, QIMR Berghofer Medical Research Institute, Brisbane, QLD 4029 Australia

Article

Publisher ID: 939

DOI: 10.1186/s12936-015-0939-1

PMC ID: 4618886

PubMed ID: 26492873

SO-VID: 996f35a0-665b-42ea-927c-2c3a7bbf9995

License:

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.