Assessment of environmental variability on malaria transmission in a malaria-endemic rural dry zone locality of Sri Lanka: The wavelet approach
Malaria is a global public health concern and its dynamic transmission is still a complex process. Malaria transmission largely depends on various factors, including demography, geography, vector dynamics, parasite reservoir, and climate. The dynamic behaviour of malaria transmission has been explai...
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| description | Malaria is a global public health concern and its dynamic transmission is still a complex process. Malaria transmission largely depends on various factors, including demography, geography, vector dynamics, parasite reservoir, and climate. The dynamic behaviour of malaria transmission has been explained using various statistical and mathematical methods. Of them, wavelet analysis is a powerful mathematical technique used in analysing rapidly changing time-series to understand disease processes in a more holistic way. The current study is aimed at identifying the pattern of malaria transmission and its variability with environmental factors in Kataragama, a malaria-endemic dry zone locality of Sri Lanka, using a wavelet approach. Monthly environmental data including total rainfall and mean water flow of the "Menik Ganga" river; mean temperature, mean minimum and maximum temperatures and mean relative humidity; and malaria cases in the Kataragama Medical Officer of Health (MOH) area were obtained from the Department of Irrigation, Department of Meteorology and Malaria Research Unit (MRU) of University of Colombo, respectively, for the period 1990 to 2005. Wavelet theory was applied to analyze these monthly time series data. There were two significant periodicities in malaria cases during the period of 1992-1995 and 1999-2000. The cross-wavelet power spectrums revealed an anti-phase correlation of malaria cases with mean temperature, minimum temperature, and water flow of "Menik Ganga" river during the period 1991-1995, while the in-phase correlation with rainfall is noticeable only during 1991-1992. Relative humidity was similarly associated with malaria cases between 1991-1992. It appears that environmental variables have contributed to a higher incidence of malaria cases in Kataragama in different time periods between 1990 and 2005. |
| doi_str_mv | 10.1371/journal.pone.0228540 |
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Malaria transmission largely depends on various factors, including demography, geography, vector dynamics, parasite reservoir, and climate. The dynamic behaviour of malaria transmission has been explained using various statistical and mathematical methods. Of them, wavelet analysis is a powerful mathematical technique used in analysing rapidly changing time-series to understand disease processes in a more holistic way. The current study is aimed at identifying the pattern of malaria transmission and its variability with environmental factors in Kataragama, a malaria-endemic dry zone locality of Sri Lanka, using a wavelet approach. Monthly environmental data including total rainfall and mean water flow of the "Menik Ganga" river; mean temperature, mean minimum and maximum temperatures and mean relative humidity; and malaria cases in the Kataragama Medical Officer of Health (MOH) area were obtained from the Department of Irrigation, Department of Meteorology and Malaria Research Unit (MRU) of University of Colombo, respectively, for the period 1990 to 2005. Wavelet theory was applied to analyze these monthly time series data. There were two significant periodicities in malaria cases during the period of 1992-1995 and 1999-2000. The cross-wavelet power spectrums revealed an anti-phase correlation of malaria cases with mean temperature, minimum temperature, and water flow of "Menik Ganga" river during the period 1991-1995, while the in-phase correlation with rainfall is noticeable only during 1991-1992. Relative humidity was similarly associated with malaria cases between 1991-1992. It appears that environmental variables have contributed to a higher incidence of malaria cases in Kataragama in different time periods between 1990 and 2005.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0228540</identifier><identifier>PMID: 32084156</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Analysis ; Artemisinin ; Biology and Life Sciences ; Climate ; Computational mathematics ; Correlation ; Demography ; Desert Climate ; Disease transmission ; Diseases ; Droughts ; Earth Sciences ; Ecology and Environmental Sciences ; Endemic Diseases ; Environment ; Environmental assessment ; Environmental factors ; Epidemics ; Geography ; Humans ; Humidity ; Hydraulic flow ; Incidence ; Malaria ; Malaria - epidemiology ; Malaria - transmission ; Mathematical analysis ; Mathematical functions ; Maximum temperatures ; Mean temperatures ; Medicine ; Medicine and Health Sciences ; Meteorological research ; Meteorology ; Minimum temperatures ; Models, Theoretical ; Parasites ; People and places ; Periodicities ; Pesticides ; Power (Philosophy) ; Public health ; Public health movements ; R&D ; Rain ; Rainfall ; Relative humidity ; Research & development ; Research and Analysis Methods ; Rivers ; Rural environments ; Rural Population - statistics & numerical data ; Seasons ; Sri Lanka - epidemiology ; Statistical methods ; Studies ; Temperature ; Time ; Time series ; Variability ; Vector-borne diseases ; Water ; Water flow ; Wavelet Analysis ; Wavelet transforms</subject><ispartof>PloS one, 2020-02, Vol.15 (2), p.e0228540</ispartof><rights>COPYRIGHT 2020 Public Library of Science</rights><rights>2020 Mahendran et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. 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Malaria transmission largely depends on various factors, including demography, geography, vector dynamics, parasite reservoir, and climate. The dynamic behaviour of malaria transmission has been explained using various statistical and mathematical methods. Of them, wavelet analysis is a powerful mathematical technique used in analysing rapidly changing time-series to understand disease processes in a more holistic way. The current study is aimed at identifying the pattern of malaria transmission and its variability with environmental factors in Kataragama, a malaria-endemic dry zone locality of Sri Lanka, using a wavelet approach. 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It appears that environmental variables have contributed to a higher incidence of malaria cases in Kataragama in different time periods between 1990 and 2005.</description><subject>Analysis</subject><subject>Artemisinin</subject><subject>Biology and Life Sciences</subject><subject>Climate</subject><subject>Computational mathematics</subject><subject>Correlation</subject><subject>Demography</subject><subject>Desert Climate</subject><subject>Disease transmission</subject><subject>Diseases</subject><subject>Droughts</subject><subject>Earth Sciences</subject><subject>Ecology and Environmental Sciences</subject><subject>Endemic Diseases</subject><subject>Environment</subject><subject>Environmental assessment</subject><subject>Environmental factors</subject><subject>Epidemics</subject><subject>Geography</subject><subject>Humans</subject><subject>Humidity</subject><subject>Hydraulic flow</subject><subject>Incidence</subject><subject>Malaria</subject><subject>Malaria - epidemiology</subject><subject>Malaria - transmission</subject><subject>Mathematical analysis</subject><subject>Mathematical functions</subject><subject>Maximum temperatures</subject><subject>Mean temperatures</subject><subject>Medicine</subject><subject>Medicine and Health Sciences</subject><subject>Meteorological research</subject><subject>Meteorology</subject><subject>Minimum temperatures</subject><subject>Models, Theoretical</subject><subject>Parasites</subject><subject>People and places</subject><subject>Periodicities</subject><subject>Pesticides</subject><subject>Power (Philosophy)</subject><subject>Public health</subject><subject>Public health movements</subject><subject>R&D</subject><subject>Rain</subject><subject>Rainfall</subject><subject>Relative humidity</subject><subject>Research & development</subject><subject>Research and Analysis Methods</subject><subject>Rivers</subject><subject>Rural environments</subject><subject>Rural Population - statistics & numerical data</subject><subject>Seasons</subject><subject>Sri Lanka - 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Malaria transmission largely depends on various factors, including demography, geography, vector dynamics, parasite reservoir, and climate. The dynamic behaviour of malaria transmission has been explained using various statistical and mathematical methods. Of them, wavelet analysis is a powerful mathematical technique used in analysing rapidly changing time-series to understand disease processes in a more holistic way. The current study is aimed at identifying the pattern of malaria transmission and its variability with environmental factors in Kataragama, a malaria-endemic dry zone locality of Sri Lanka, using a wavelet approach. Monthly environmental data including total rainfall and mean water flow of the "Menik Ganga" river; mean temperature, mean minimum and maximum temperatures and mean relative humidity; and malaria cases in the Kataragama Medical Officer of Health (MOH) area were obtained from the Department of Irrigation, Department of Meteorology and Malaria Research Unit (MRU) of University of Colombo, respectively, for the period 1990 to 2005. Wavelet theory was applied to analyze these monthly time series data. There were two significant periodicities in malaria cases during the period of 1992-1995 and 1999-2000. The cross-wavelet power spectrums revealed an anti-phase correlation of malaria cases with mean temperature, minimum temperature, and water flow of "Menik Ganga" river during the period 1991-1995, while the in-phase correlation with rainfall is noticeable only during 1991-1992. Relative humidity was similarly associated with malaria cases between 1991-1992. It appears that environmental variables have contributed to a higher incidence of malaria cases in Kataragama in different time periods between 1990 and 2005.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>32084156</pmid><doi>10.1371/journal.pone.0228540</doi><tpages>e0228540</tpages><orcidid>https://orcid.org/0000-0003-3079-4422</orcidid><orcidid>https://orcid.org/0000-0001-9216-2071</orcidid><oa>free_for_read</oa></addata></record> |
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| recordid | cdi_plos_journals_2360073346 |
| source | Public Library of Science (PLoS) Journals Open Access; PubMed (Medline); MEDLINE; DOAJ Directory of Open Access Journals; EZB-FREE-00999 freely available EZB journals; Free Full-Text Journals in Chemistry |
| subjects | Analysis Artemisinin Biology and Life Sciences Climate Computational mathematics Correlation Demography Desert Climate Disease transmission Diseases Droughts Earth Sciences Ecology and Environmental Sciences Endemic Diseases Environment Environmental assessment Environmental factors Epidemics Geography Humans Humidity Hydraulic flow Incidence Malaria Malaria - epidemiology Malaria - transmission Mathematical analysis Mathematical functions Maximum temperatures Mean temperatures Medicine Medicine and Health Sciences Meteorological research Meteorology Minimum temperatures Models, Theoretical Parasites People and places Periodicities Pesticides Power (Philosophy) Public health Public health movements R&D Rain Rainfall Relative humidity Research & development Research and Analysis Methods Rivers Rural environments Rural Population - statistics & numerical data Seasons Sri Lanka - epidemiology Statistical methods Studies Temperature Time Time series Variability Vector-borne diseases Water Water flow Wavelet Analysis Wavelet transforms |
| title | Assessment of environmental variability on malaria transmission in a malaria-endemic rural dry zone locality of Sri Lanka: The wavelet approach |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-28T09%3A21%3A21IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_plos_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Assessment%20of%20environmental%20variability%20on%20malaria%20transmission%20in%20a%20malaria-endemic%20rural%20dry%20zone%20locality%20of%20Sri%20Lanka:%20The%20wavelet%20approach&rft.jtitle=PloS%20one&rft.au=Mahendran,%20Rahini&rft.date=2020-02-21&rft.volume=15&rft.issue=2&rft.spage=e0228540&rft.pages=e0228540-&rft.issn=1932-6203&rft.eissn=1932-6203&rft_id=info:doi/10.1371/journal.pone.0228540&rft_dat=%3Cgale_plos_%3EA614629581%3C/gale_plos_%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2360073346&rft_id=info:pmid/32084156&rft_galeid=A614629581&rft_doaj_id=oai_doaj_org_article_2d84acdb83314773819b905ec4ba8dd3&rfr_iscdi=true |