Modelling the incidence of Plasmodium vivax and Plasmodium falciparum malaria in Afghanistan 2006-2009
Modelling the incidence of Plasmodium vivax and Plasmodium falciparum malaria in Afghanistan 2006-2009
Background: Identifying areas that support high malaria risks and where populations lack access to health care is central to reducing the burden in Afghanistan. This study investigated the incidence of Plasmodium vivax and Plasmodium falciparum using routine data to help focus malaria interventions.
Methods: To estimate incidence, the study modelled utilisation of the public health sector using fever treatment data from the 2012 national Malaria Indicator Survey. A probabilistic measure of attendance was applied to population density metrics to define the proportion of the population within catchment of a public health facility. Malaria data were used in a Bayesian spatio-temporal conditional-autoregressive model with ecological or environmental covariates, to examine the spatial and temporal variation of incidence.
Findings: From the analysis of healthcare utilisation, over 80% of the population was within 2 hours’ travel of the nearest public health facility, while 64.4% were within 30 minutes’ travel. The mean incidence of P. vivax in 2009 was 5.4 (95% Crl 3.2–9.2) cases per 1000 population compared to 1.2 (95% Crl 0.4–2.9) cases per 1000 population for P. falciparum. P. vivax peaked in August while P. falciparum peaked in November. 32% of the estimated 30.5 million people lived in regions where annual incidence was at least 1 case per 1,000 population of P. vivax; 23.7% of the population lived in areas where annual P. falciparum case incidence was at least 1 per 1000.
Conclusion: This study showed how routine data can be combined with household survey data to model malaria incidence. The incidence of both P. vivax and P. falciparum in Afghanistan remain low but the co-distribution of both parasites and the lag in their peak season provides challenges to malaria control in Afghanistan. Future improved case definition to determine levels of imported risks may be useful for the elimination ambitions in Afghanistan.
Alegana, Victor
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Wright, J.A.
94990ecf-f8dd-4649-84f2-b28bf272e464
Nahzat, S.
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Butt, W.
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Sediqi, A.
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Habib, N.
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Snow, R.
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Atkinson, P.M.
96e96579-56fe-424d-a21c-17b6eed13b0b
Noor, A.
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17 July 2014
Alegana, Victor
f5bd6ab7-459e-4122-984f-2bdb5f906d82
Wright, J.A.
94990ecf-f8dd-4649-84f2-b28bf272e464
Nahzat, S.
ab9f0a1c-1dcb-4cdd-b7f8-e54f84a69b16
Butt, W.
5873f518-e8ad-46c4-a47f-c1bd174b69e0
Sediqi, A.
e1d200f5-f2f0-4c71-9da8-4d919c38049e
Habib, N.
6a66994c-082c-4322-a15e-d20e9d156c49
Snow, R.
6116188a-1ac9-492a-aac0-9cdd3479deeb
Atkinson, P.M.
96e96579-56fe-424d-a21c-17b6eed13b0b
Noor, A.
f9947236-57a3-4092-9ba9-3883eb1ec48e
Alegana, Victor, Wright, J.A., Nahzat, S., Butt, W., Sediqi, A., Habib, N., Snow, R., Atkinson, P.M. and Noor, A.
(2014)
Modelling the incidence of Plasmodium vivax and Plasmodium falciparum malaria in Afghanistan 2006-2009.
PLoS ONE, 9 (7).
(doi:10.1371/journal.pone.0102304).
Abstract
Background: Identifying areas that support high malaria risks and where populations lack access to health care is central to reducing the burden in Afghanistan. This study investigated the incidence of Plasmodium vivax and Plasmodium falciparum using routine data to help focus malaria interventions.
Methods: To estimate incidence, the study modelled utilisation of the public health sector using fever treatment data from the 2012 national Malaria Indicator Survey. A probabilistic measure of attendance was applied to population density metrics to define the proportion of the population within catchment of a public health facility. Malaria data were used in a Bayesian spatio-temporal conditional-autoregressive model with ecological or environmental covariates, to examine the spatial and temporal variation of incidence.
Findings: From the analysis of healthcare utilisation, over 80% of the population was within 2 hours’ travel of the nearest public health facility, while 64.4% were within 30 minutes’ travel. The mean incidence of P. vivax in 2009 was 5.4 (95% Crl 3.2–9.2) cases per 1000 population compared to 1.2 (95% Crl 0.4–2.9) cases per 1000 population for P. falciparum. P. vivax peaked in August while P. falciparum peaked in November. 32% of the estimated 30.5 million people lived in regions where annual incidence was at least 1 case per 1,000 population of P. vivax; 23.7% of the population lived in areas where annual P. falciparum case incidence was at least 1 per 1000.
Conclusion: This study showed how routine data can be combined with household survey data to model malaria incidence. The incidence of both P. vivax and P. falciparum in Afghanistan remain low but the co-distribution of both parasites and the lag in their peak season provides challenges to malaria control in Afghanistan. Future improved case definition to determine levels of imported risks may be useful for the elimination ambitions in Afghanistan.
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e-pub ahead of print date: 17 July 2014
Published date: 17 July 2014
Organisations:
Global Env Change & Earth Observation, WorldPop
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Local EPrints ID: 368338
URI: http://eprints.soton.ac.uk/id/eprint/368338
ISSN: 1932-6203
PURE UUID: 7832779c-b008-4c80-8575-374642079d34
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Date deposited: 28 Aug 2014 10:54
Last modified: 15 Mar 2024 03:21
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Contributors
Author:
S. Nahzat
Author:
W. Butt
Author:
A. Sediqi
Author:
N. Habib
Author:
R. Snow
Author:
P.M. Atkinson
Author:
A. Noor
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