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Temporal Variations and Associated Remotely Sensed Environmental Variables of Dengue Fever in Chitwan District, Nepal

Authors: Bipin Kumar Acharya; Chunxiang Cao; Min Xu; Laxman Khanal; Shahid Naeem; Shreejana Pandit;

Temporal Variations and Associated Remotely Sensed Environmental Variables of Dengue Fever in Chitwan District, Nepal

Abstract

Dengue fever is one of the leading public health problems of tropical and subtropical countries across the world. Transmission dynamics of dengue fever is largely affected by meteorological and environmental factors, and its temporal pattern generally peaks in hot-wet periods of the year. Despite this continuously growing problem, the temporal dynamics of dengue fever and associated potential environmental risk factors are not documented in Nepal. The aim of this study was to fill this research gap by utilizing epidemiological and earth observation data in Chitwan district, one of the frequent dengue outbreak areas of Nepal. We used laboratory confirmed monthly dengue cases as a dependent variable and a set of remotely sensed meteorological and environmental variables as explanatory factors to describe their temporal relationship. Descriptive statistics, cross correlation analysis, and the Poisson generalized additive model were used for this purpose. Results revealed that dengue fever is significantly associated with satellite estimated precipitation, normalized difference vegetation index (NDVI), and enhanced vegetation index (EVI) synchronously and with different lag periods. However, the associations were weak and insignificant with immediate daytime land surface temperature (dLST) and nighttime land surface temperature (nLST), but were significant after 4&ndash

s Information Criterion (AIC) and maximum R-squared. The best fit model further significantly improved after including delayed effects in the model. The predicted cases were reasonably accurate based on the comparison of 10-fold cross validation and observed cases. The lagged association found in this study could be useful for the development of remote sensing-based early warning forecasts of dengue fever.

5 months. Conclusively, the selected Poisson generalized additive model based on the precipitation, dLST, and NDVI explained the largest variation in monthly distribution of dengue fever with minimum Akaike&rsquo

Subjects by Vocabulary

Microsoft Academic Graph classification: media_common.quotation_subject Poisson distribution Normalized Difference Vegetation Index Dengue fever symbols.namesake Statistics medicine Time series media_common Variables Generalized additive model Enhanced vegetation index medicine.disease Geography symbols Akaike information criterion

Library of Congress Subject Headings: lcsh:G1-922 lcsh:Geography (General)

Keywords

Geography, Planning and Development, remote sensing, Nepal, Earth and Planetary Sciences (miscellaneous), dengue fever, Computers in Earth Sciences, early warning, Geography (General), time series model, G1-922

54 references, page 1 of 6

1. Wilder-Smith, A.; Murray, N.A.E.; Quam, M.B. Epidemiology of dengue: Past, present and future prospects. Clin. Epidemiol. 2013, 5, 299-309. [CrossRef] [PubMed]

2. Bhatt, S.; Gething, P.W.; Brady, O.J.; Messina, J.P.; Farlow, A.W.; Moyes, C.L.; Drake, J.M.; Brownstein, J.S.; Hoen, A.G.; Sankoh, O.; et al. The global distribution and burden of dengue. Nature 2013, 496, 504-507. [CrossRef] [PubMed] [OpenAIRE]

3. Messina, J.P.; Brady, O.J.; Pigott, D.M.; Golding, N.; Kraemer, M.U.G.; Scott, T.W.; Wint, G.R.W.; Smith, D.L.; Hay, S.I. The many projected futures of dengue. Nat. Rev. Microbiol. 2015, 13, 230-239. [CrossRef] [PubMed]

4. Naish, S.; Dale, P.; Mackenzie, J.S.; McBride, J.; Mengersen, K.; Tong, S. Climate change and dengue: A critical and systematic review of quantitative modelling approaches. BMC Infect. Dis. 2014, 14, 167. [CrossRef] [PubMed]

5. Regis, L.N.; Acioli, R.V.; Silveira, J.C.; de Melo-Santos, M.A.V.; da Cunha, M.C.S.; Souza, F.; Batista, C.A.V.; Barbosa, R.M.R.; de Oliveira, C.M.F.; Ayres, C.F.J.; et al. Characterization of the spatial and temporal dynamics of the dengue vector population established in urban areas of Fernando de Noronha, a Brazilian oceanic island. Acta Trop. 2014, 137, 80-87. [CrossRef] [PubMed]

6. Morin, C.W.; Comrie, A.C.; Ernst, K. Climate and Dengue Transmission: Evidence and Implications. Environ. Health Perspect. 2013, 121, 1264-1272. [CrossRef] [PubMed] [OpenAIRE]

7. Méndez-Lázaro, P.; Muller-Karger, F.; Otis, D.; McCarthy, M.; Peña-Orellana, M. Assessing Climate Variability Effects on Dengue Incidence in San Juan, Puerto Rico. Int. J. Environ. Res. Public. Health 2014, 11, 9409-9428. [CrossRef] [PubMed]

8. Gubler, D.J. Epidemic dengue/dengue hemorrhagic fever as a public health, social and economic problem in the 21st century. Trends Microbiol. 2002, 10, 100-103. [CrossRef]

9. Eastin, M.D.; Delmelle, E.; Casas, I.; Wexler, J.; Self, C. Intra- and Interseasonal Autoregressive Prediction of Dengue Outbreaks Using Local Weather and Regional Climate for a Tropical Environment in Colombia. Am. J. Trop. Med. Hyg. 2014, 91, 598-610. [CrossRef] [PubMed] [OpenAIRE]

10. Gharbi, M.; Quenel, P.; Gustave, J.; Cassadou, S.; Ruche, G.L.; Girdary, L.; Marrama, L. Time series analysis of dengue incidence in Guadeloupe, French West Indies: Forecasting models using climate variables as predictors. BMC Infect. Dis. 2011, 11, 166. [CrossRef] [PubMed] [OpenAIRE]

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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    2
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Average
Average
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