Rapid assessment of malaria transmission using age-specific sero-conversion rates - PubMed (original) (raw)

. 2009 Jun 29;4(6):e6083.

doi: 10.1371/journal.pone.0006083.

Roly Gosling, Jamie Griffin, Samwel Gesase, Joseph Campo, Ramadan Hashim, Paul Masika, Jacklin Mosha, Teun Bousema, Seif Shekalaghe, Jackie Cook, Patrick Corran, Azra Ghani, Eleanor M Riley, Chris Drakeley

Affiliations

Rapid assessment of malaria transmission using age-specific sero-conversion rates

Laveta Stewart et al. PLoS One. 2009.

Abstract

Background: Malaria transmission intensity is a crucial determinant of malarial disease burden and its measurement can help to define health priorities. Rapid, local estimates of transmission are required to focus resources better but current entomological and parasitological methods for estimating transmission intensity are limited in this respect. An alternative is determination of antimalarial antibody age-specific sero-prevalence to estimate sero-conversion rates (SCR), which have been shown to correlate with transmission intensity. This study evaluated SCR generated from samples collected from health facility attendees as a tool for a rapid assessment of malaria transmission intensity.

Methodology and principal findings: The study was conducted in north east Tanzania. Antibodies to Plasmodium falciparum merozoite antigens MSP-1(19) and AMA-1 were measured by indirect ELISA. Age-specific antibody prevalence was analysed using a catalytic conversion model based on maximum likelihood to generate SCR. A pilot study, conducted near Moshi, found SCRs for AMA-1 were highly comparable between samples collected from individuals in a conventional cross-sectional survey and those collected from attendees at a local health facility. For the main study, 3885 individuals attending village health facilities in Korogwe and Same districts were recruited. Both malaria parasite prevalence and sero-positivity were higher in Korogwe than in Same. MSP-1(19) and AMA-1 SCR rates for Korogwe villages ranged from 0.03 to 0.06 and 0.07 to 0.21 respectively. In Same district there was evidence of a recent reduction in transmission, with SCR among those born since 1998 [MSP-1(19) 0.002 to 0.008 and AMA-1 0.005 to 0.014 ] being 5 to 10 fold lower than among individuals born prior to 1998 [MSP-1(19) 0.02 to 0.04 and AMA-1 0.04 to 0.13]. Current health facility specific estimates of SCR showed good correlations with malaria incidence rates in infants in a contemporaneous clinical trial (MSP-1(19) r(2) = 0.78, p<0.01 & AMA-1 r(2) = 0.91, p<0.001).

Conclusions: SCRs generated from age-specific anti-malarial antibody prevalence data collected via health facility surveys were robust and credible. Analysis of SCR allowed detection of a recent drop in malaria transmission in line with recent data from other areas in the region. This health facility-based approach represents a potential tool for rapid assessment of recent trends in malaria transmission intensity, generating valuable data for local and national malaria control programs to target, monitor and evaluate their control strategies.

PubMed Disclaimer

Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Figure 1

Figure 1. Map showing the study area: Squares mark major towns, circles mark villages with study dispensaries.

Figure 2

Figure 2. Age sero-prevalence plots for antibody responses to P. falciparum parasite antigens MSP-119 (fig 2a) and AMA-1 (figure 2b) from the pilot study (Msitu wa Tembo).

Open circles (and confidence limits) represent observed age group specific sero-prevalence points for the cross sectional survey. The dotted line represents a maximum likelihood fit using these data. The full triangles and unbroken line represent observed sero-prevalence points and fitted line for the health facility surveys.

Figure 3

Figure 3. Age sero-prevalence plots for MSP-119 and AMA-1 fitted by maximum likelihood with a single force of infection for the dispensaries in the Kili-IPTi study.

Plot a) MSP-119 Same district; b) AMA-1 Same district; c) MSP-119 Korogwe district and d) AMA-1 Korogwe district. Black triangles represent observed data and black lines predicted values. Dotted black lines represent upper and lower 95% CI for the predicted SCR.

Figure 4

Figure 4. Univariate profile likelihood to evaluate the time at which sero-conversion rates changed.

Same region fits are represented in a) for MSP-119 fits and b) for AMA-1. The broken black line is the 95th percentile of the Chi-squared on 1 degree of freedom below the maximum. The two points at which this line crosses the log-likelihood profile are used to determine an approximate 95% confidence interval for the time since the change in SCR i.e. 11–18 years for MSP-119 and 6 to 14 years for AMA-1. The equivalent plots for Korogwe are shown in c) for MSP-119 and d) for AMA-1.

Figure 5

Figure 5. Age sero-prevalence plots for MSP-119(a) and AMA-1 (b) fitted by maximum likelihood with a two forces of infection for Same district.

Black triangles represent observed data and black lines predicted values. Dotted black lines represent upper and lower 95% CI for the predicted SCR.

Figure 6

Figure 6. Current sero-conversion rates and clinical malaria incidence rates in the IPTi placebo cohort for each health facility: (a) for MSP-119 and (b) for AMA-1.

Vertical bars indicate the 95% CI for SCR and horizontal bars indicate the 95% CI for malaria incidence. Fitted lines represent linear regression plots. R2 values for MSP-119 and AMA are 0.78 and 0.91, respectively.

Similar articles

Cited by

References

    1. Bhattarai A, Ali AS, Kachur SP, Martensson A, Abbas AK, et al. Impact of artemisinin-based combination therapy and insecticide-treated nets on malaria burden in Zanzibar. PLoS Med. 2007;4:e309. - PMC - PubMed
    1. Fegan GW, Noor AM, Akhwale WS, Cousens S, Snow RW. Effect of expanded insecticide-treated bednet coverage on child survival in rural Kenya: a longitudinal study. Lancet. 2007;370:1035–1039. - PMC - PubMed
    1. Sharp BL, Kleinschmidt I, Streat E, Maharaj R, Barnes KI, et al. Seven years of regional malaria control collaboration–Mozambique, South Africa, and Swaziland. Am J Trop Med Hyg. 2007;76:42–47. - PMC - PubMed
    1. Guerra CA, Hay SI, Lucioparedes LS, Gikandi PW, Tatem AJ, et al. Assembling a global database of malaria parasite prevalence for the Malaria Atlas Project. Malar J. 2007;6:17. - PMC - PubMed
    1. Okiro EA, Hay SI, Gikandi PW, Sharif SK, Noor AM, et al. The decline in paediatric malaria admissions on the coast of Kenya. Malar J. 2007;6:151. - PMC - PubMed

Publication types

MeSH terms

Substances

LinkOut - more resources