Remotely-sensed, nocturnal, dew point correlates with malaria transmission in Southern Province, Zambia: a time-series study
Nygren, David LU
; Stoyanov, Cristina
; Lewold, Clemens
; Månsson, Fredrik
LU
; Miller, John
; Kamanga, Aniset
and Shiff, Clive J.
(2014)
In Malaria Journal
13.
- Abstract
- Background: Plasmodium falciparum transmission has decreased significantly in Zambia in the last decade. The malaria transmission is influenced by environmental variables. Incorporation of environmental variables in models of malaria transmission likely improves model fit and predicts probable trends in malaria disease. This work is based on the hypothesis that remotely-sensed environmental factors, including nocturnal dew point, are associated with malaria transmission and sustain foci of transmission during the low transmission season in the Southern Province of Zambia. Methods: Thirty-eight rural health centres in Southern Province, Zambia were divided into three zones based on transmission patterns. Correlations between weekly malaria... (More)
- Background: Plasmodium falciparum transmission has decreased significantly in Zambia in the last decade. The malaria transmission is influenced by environmental variables. Incorporation of environmental variables in models of malaria transmission likely improves model fit and predicts probable trends in malaria disease. This work is based on the hypothesis that remotely-sensed environmental factors, including nocturnal dew point, are associated with malaria transmission and sustain foci of transmission during the low transmission season in the Southern Province of Zambia. Methods: Thirty-eight rural health centres in Southern Province, Zambia were divided into three zones based on transmission patterns. Correlations between weekly malaria cases and remotely-sensed nocturnal dew point, nocturnal land surface temperature as well as vegetation indices and rainfall were evaluated in time-series analyses from 2012 week 19 to 2013 week 36. Zonal as well as clinic-based, multivariate, autoregressive, integrated, moving average ( ARIMAX) models implementing environmental variables were developed to model transmission in 2011 week 19 to 2012 week 18 and forecast transmission in 2013 week 37 to week 41. Results: During the dry, low transmission season significantly higher vegetation indices, nocturnal land surface temperature and nocturnal dew point were associated with the areas of higher transmission. Environmental variables improved ARIMAX models. Dew point and normalized differentiated vegetation index were significant predictors and improved all zonal transmission models. In the high-transmission zone, this was also seen for land surface temperature. Clinic models were improved by adding dew point and land surface temperature as well as normalized differentiated vegetation index. The mean average error of prediction for ARIMAX models ranged from 0.7 to 33.5%. Forecasts of malaria incidence were valid for three out of five rural health centres; however, with poor results at the zonal level. Conclusions: In this study, the fit of ARIMAX models improves when environmental variables are included. There is a significant association of remotely-sensed nocturnal dew point with malaria transmission. Interestingly, dew point might be one of the factors sustaining malaria transmission in areas of general aridity during the dry season. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/4602389
- author
- Nygren, David
LU
; Stoyanov, Cristina
; Lewold, Clemens
; Månsson, Fredrik
LU
; Miller, John
; Kamanga, Aniset
and Shiff, Clive J.
- organization
- publishing date
- 2014
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Malaria, ARIMAX, Dew point, Remote sensing, Environment
- in
- Malaria Journal
- volume
- 13
- article number
- 231
- publisher
- BioMed Central (BMC)
- external identifiers
-
- wos:000338889000002
- scopus:84902051546
- pmid:24927747
- ISSN
- 1475-2875
- DOI
- 10.1186/1475-2875-13-231
- language
- English
- LU publication?
- yes
- id
- 58ceaaff-7429-47fb-9606-226627340af2 (old id 4602389)
- date added to LUP
- 2016-04-01 13:02:41
- date last changed
- 2022-01-27 17:00:51
@article{58ceaaff-7429-47fb-9606-226627340af2,
abstract = {{Background: Plasmodium falciparum transmission has decreased significantly in Zambia in the last decade. The malaria transmission is influenced by environmental variables. Incorporation of environmental variables in models of malaria transmission likely improves model fit and predicts probable trends in malaria disease. This work is based on the hypothesis that remotely-sensed environmental factors, including nocturnal dew point, are associated with malaria transmission and sustain foci of transmission during the low transmission season in the Southern Province of Zambia. Methods: Thirty-eight rural health centres in Southern Province, Zambia were divided into three zones based on transmission patterns. Correlations between weekly malaria cases and remotely-sensed nocturnal dew point, nocturnal land surface temperature as well as vegetation indices and rainfall were evaluated in time-series analyses from 2012 week 19 to 2013 week 36. Zonal as well as clinic-based, multivariate, autoregressive, integrated, moving average ( ARIMAX) models implementing environmental variables were developed to model transmission in 2011 week 19 to 2012 week 18 and forecast transmission in 2013 week 37 to week 41. Results: During the dry, low transmission season significantly higher vegetation indices, nocturnal land surface temperature and nocturnal dew point were associated with the areas of higher transmission. Environmental variables improved ARIMAX models. Dew point and normalized differentiated vegetation index were significant predictors and improved all zonal transmission models. In the high-transmission zone, this was also seen for land surface temperature. Clinic models were improved by adding dew point and land surface temperature as well as normalized differentiated vegetation index. The mean average error of prediction for ARIMAX models ranged from 0.7 to 33.5%. Forecasts of malaria incidence were valid for three out of five rural health centres; however, with poor results at the zonal level. Conclusions: In this study, the fit of ARIMAX models improves when environmental variables are included. There is a significant association of remotely-sensed nocturnal dew point with malaria transmission. Interestingly, dew point might be one of the factors sustaining malaria transmission in areas of general aridity during the dry season.}},
author = {{Nygren, David and Stoyanov, Cristina and Lewold, Clemens and Månsson, Fredrik and Miller, John and Kamanga, Aniset and Shiff, Clive J.}},
issn = {{1475-2875}},
keywords = {{Malaria; ARIMAX; Dew point; Remote sensing; Environment}},
language = {{eng}},
publisher = {{BioMed Central (BMC)}},
series = {{Malaria Journal}},
title = {{Remotely-sensed, nocturnal, dew point correlates with malaria transmission in Southern Province, Zambia: a time-series study}},
url = {{https://lup.lub.lu.se/search/files/3125239/8310744.pdf}},
doi = {{10.1186/1475-2875-13-231}},
volume = {{13}},
year = {{2014}},
}