A longitudinal study of malaria associated with deforestation in Sonitpur district of Assam, India

Assam–Arunachal forest fringed foothill area is endemic for malaria incidence. The present study deals with the temporal analysis of malaria incidence and determines its association with deforestation in 24 villages along the Assam–Arunachal forest
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  This article was downloaded by: [Manash J. Nath]On: 30 January 2012, At: 01:24Publisher: Taylor & FrancisInforma Ltd Registered in England and Wales Registered Number: 1072954 Registeredoffice: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UK Geocarto International Publication details, including instructions for authors andsubscription information: A longitudinal study of malariaassociated with deforestation inSonitpur district of Assam, India Manash J. Nath a  , Ashok Bora b  , P.K. Talukdar a  , N.G. Das a  ,Sunil Dhiman a  , I. Baruah a  & Lokendra Singh aa  Defence Research Laboratory (DRDO), Post Bag No. 2, Tezpur,Sonitpur, Assam, 784001, India b  Department of Geography, Gauhati University, Guwahati, Assam,781014, IndiaAvailable online: 15 Aug 2011 To cite this article:  Manash J. Nath, Ashok Bora, P.K. Talukdar, N.G. Das, Sunil Dhiman, I. Baruah& Lokendra Singh (2012): A longitudinal study of malaria associated with deforestation in Sonitpurdistrict of Assam, India, Geocarto International, 27:1, 79-88 To link to this article: PLEASE SCROLL DOWN FOR ARTICLEFull terms and conditions of use: article may be used for research, teaching, and private study purposes. Anysubstantial or systematic reproduction, redistribution, reselling, loan, sub-licensing,systematic supply, or distribution in any form to anyone is expressly forbidden.The publisher does not give any warranty express or implied or make any representationthat the contents will be complete or accurate or up to date. The accuracy of anyinstructions, formulae, and drug doses should be independently verified with primarysources. The publisher shall not be liable for any loss, actions, claims, proceedings,demand, or costs or damages whatsoever or howsoever caused arising directly orindirectly in connection with or arising out of the use of this material.  A longitudinal study of malaria associated with deforestation inSonitpur district of Assam, India Manash J. Nath a *, Ashok Bora b , P.K. Talukdar a ,N.G. Das a , Sunil Dhiman a , I. Baruah a and Lokendra Singh a a Defence Research Laboratory (DRDO), Post Bag No. 2, Tezpur, Sonitpur, Assam 784001,India;  b Department of Geography, Gauhati University, Guwahati, Assam 781014, India ( Received 30 March 2011; final version received 8 August 2011 )Assam–Arunachal forest fringed foothill area is endemic for malaria incidence.The present study deals with the temporal analysis of malaria incidence anddetermines its association with deforestation in 24 villages along the Assam– Arunachal forest fringed foothill area of Sonitpur district of Assam. Malariaepidemiological survey has been carried out in the study area from the year 1994to 2005. Remote sensing (RS) technique has been used to map the areas of forestchanges from the year 2000 to 2005. Geographical information system (GIS) wasused to map the malaria incidence and forest cover. The study villages areendemic to malaria infections and there was increasing trend of malaria incidenceover the years. The slide positivity rate (SPR) ranged from 5.1% in 1997 to 44.4%in 2005. The percentage forest cover decreased significantly from 23.6% during2000 to 15.4% during 2005, whereas SPR was increased during 2000–2005. Thepresent study is the first attempt to understand the role of deforestation in malariaincidence using RS and GIS in the north-eastern region of India at a micro-geographic level. The study suggests that the area is endemic to malariatransmission. The decrease in forest cover is a serious ecological concern besidesits role in elevating the malaria incidence in the study area. Keywords:  epidemiology; slide positivity rate; remote sensing; geographicalinformation system Introduction In recent years, the climatic change and its association with changing pattern of diseases is a major concern for the scientific community. Deforestation has been amajor factor in contributing changes in the micro-climate of an area (Berbet andCosta 2003, Yan  et al.  2006). In tropical region, the adverse effect of deforestationincludes increase in soil erosion and changing pattern of vector-borne diseases likemalaria, dengue, etc., which have attracted the attention of environment and healthauthorities (Mas 1999, Patz  et al.  2000, 2006, Afrane  et al.  2008).The state of Assam in the north-east India has rich biodiversity and has beenendemic for perennial malaria transmission (Dhiman  et al.  2010). However,indiscriminate deforestation in the state has caused considerable havoc in recentfew years. The forest loss in Assam from 2005 to 2007 was 66 km 2 as reported by the *Corresponding author. Email: Geocarto International  Vol. 27, No. 1, February 2012, 79–88 ISSN 1010-6049 print/ISSN 1752-0762 online   2012 Taylor & Francis    D  o  w  n   l  o  a   d  e   d   b  y   [   M  a  n  a  s   h   J .   N  a   t   h   ]  a   t   0   1  :   2   4   3   0   J  a  n  u  a  r  y   2   0   1   2  Forest Survey of India, Ministry of Environment and Forests (2009). An overallloss of 232.19 km 2 (28.65%) of forest was recorded from 1994 to 2001 in Sonitpurdistrict of Assam alone (Srivastava  et al.  2002). The forest loss in Charduar reserveforest and Balipara reserve forest of Sonitpur district reported 60% and 40%loss, respectively between 1994 and 1999 (Kushwaha and Hazarika 2004). Thedeforestation, human resettlement and developmental programmes singly or incombination increased the morbidity and mortality from emergent parasitic diseases(Patz  et al.  2000). The state of Assam is very much vulnerable to malaria because of its location in the tropical region with humid climatic condition throughout the year(Mohapatra  et al.  2001, Dev  et al.  2004, Pardal  et al.  2009, Dhiman  et al.  2010).Despite of taking many preventive measures in Assam, the transmission of malariacontinues to be uninterrupted and has increased in recent times. Focal malariaoutbreaks are of common occurrence especially in forest fringed villages on Assam– Arunachal Pradesh border occupied by new settlers (Das  et al.  2002). These areashave faced vast ecological changes due to deforestation in recent years creatingconsiderable mosquitogenic conditions (Das  et al.  2004).The geographical information system (GIS) has drawn considerable attention incomprehending and visualizing the status of vector-borne diseases (Hay and Lennon1999, Kobayashi  et al.  2001, Srivastava  et al.  2004, Ceccato  et al.  2005). It offersgood opportunities to monitor regional ecosystem processes in tropical environ-ments that are undergoing rapid changes (Sader  et al.  1990). Satellite data combinedwith GIS-based analysis are being used for rapid and precise study of environmentfor many areas (Washino and Wood 1994, Sharma  et al.  1996, Ceccato  et al.  2005).Normalized Difference Vegetation Index (NDVI) is the well-known and widely usedindex to detect live green plant canopies in multi-spectral remote sensing (RS) data.It is important to understand the relationship between NDVI values and the habitatsof the vector mosquitoes using high-resolution satellite images to implement detailedforecasts for malaria endemic areas (Nihei  et al.  2002).The objectives of the present study were to review the malaria situation in thelight of forest cover retrospectively for the years between 1994 and 2005 and tosketch out the importance of deforestation in malaria incidence in the forest fringedareas of Sonitpur. The present study will help in formulating the malaria controlstrategy with speculation of the possible role of forests in malaria transmission. Materials and methods Study area The study area is located in the north-western part of Sonitpur district, Assamcovering foothill areas of the eastern Himalayas, which borders Arunachal Pradeshextending from 92 8 20 0 E longitude to 92 8 53 0 E longitude and 26 8 42 0 N latitude to27 8 02 0 N latitude (Figure 1). The average temperature during summer is from 32 to35 8  C and 15 to 20 8 C in winter, whereas average annual rainfall ranges between170 and 220 cm (Baruah  et al.  2007). The monsoon period starts from June toSeptember, though the rainfall starts from the early part of April. A number of reserve forests are located in the foothills of the district covering 1417 sq km(Economic survey Assam 2007–2008). The prevailing climatic condition of thisregion helps in breeding and proliferation of vector mosquitoes. Various ethnicgroups like Assamese, Bodo, Nepali and Aadivasi are main inhabitants with verylow socio-economic condition.80  M.J. Nath  et al.    D  o  w  n   l  o  a   d  e   d   b  y   [   M  a  n  a  s   h   J .   N  a   t   h   ]  a   t   0   1  :   2   4   3   0   J  a  n  u  a  r  y   2   0   1   2  Epidemiological data collection The malaria epidemiological surveys have been carried out since 1994 in 24 foothillvillages of Sonitpur by active fever surveillance, which includes door to doorcollection of thick and thin blood smears on glass slides by finger prick method frompersons having fever history for the past 10–14 days. For our convenience, the studyvillages were divided into six patches based on their location (Table 1). Patch Icomprised six villages namely Hoograjuli, Sapai majgaon, Sapai rawmari, Balisuti,Dipabasti and Pochabasti that are located in the western part of the study area.Patch II consisted of a group of small resettlements in the foothill area situated in thenorth-western part of the study area. Patch III constituted Bengenajuli, Naharani,Gulai centre, Kalamati, Dighaljuli, Rikamari and Jiagabharu villages, whereasRamnathpur, Belsiri, Nonkebelsiri, Barbeel, Dhankhona, Bandarhagi and Dheki-pelua villages were included in patch IV. Patch V, which is located in the north-eastof the study area, included Chatai and Gamani villages, while Charduar villageconstituted Patch VI. The cases reported to the Government health centres were alsoincluded in the study. Figure 1. Study area showing the forest cover and study villages in patches. Geocarto International   81    D  o  w  n   l  o  a   d  e   d   b  y   [   M  a  n  a  s   h   J .   N  a   t   h   ]  a   t   0   1  :   2   4   3   0   J  a  n  u  a  r  y   2   0   1   2  The collected thick and thin blood smears were stained with Giemsa stain andexamined under microscope for malaria parasite identification. The malaria slidepositivity rate (SPR) was calculated from the collected data and used to revealthe malaria. Epidemiological surveys were carried out throughout every year in thesummer and monsoon, when malaria cases increased. Preparation of GIS and RS maps Topological maps (scale ¼ 1:50,000) of the study area acquired from the Survey of India (Govt. of India) were scanned and georeferenced in the GIS environment withthe help of ESRI 1 ArcMap TM 9.2 software, Redlands, CA. Base map representingdifferent layers such as forest covers, water bodies, roads, villages, etc. of the studyarea was prepared from the toposheets. Global positioning system (GPS) survey wascarried out with the help of a hand-held Garmin iQue 1 M5 GPS, to locate the studyvillages for mapping.To understand the impact of deforestation on distribution of malaria in the studyarea, satellite imageries were used and NDVI was calculated from each of thesatellite imagery to observe the change in the vegetation cover. Satellite imageries of Indian remote sensing satellite (IRS) were taken from National remote sensing centre(NRSC) and defence electronics application laboratory (DEAL), India. IRS 1DLISS-III digital data pertaining to year 2000, 2003 and 2005 of the study area wereused to monitor the changes in forest cover. Based on the geographically correctedtoposheets, the satellite images were georeferenced to rectify the images using morenumber of ground control points (GCP) with the help of PCI Geomatica v 9.0software. NDVI was calculated using the software PCI Geomatica. The NDVImeasures based on solar radiation in the near infrared (NIR) and visible (VIS)wavelengths have been estimated using the following mathematical formula:NDVI  ¼ ð NIR    VIS Þ = ð NIR  þ  VIS Þ : In the software NDVI for IRS 1D LISS III, satellite data were calculated byNDVI  ¼ ð Band 3    Band 2 Þ = ð Band 3  þ  Band 2 Þ : Table 1. Slide positivity rate (SPR in %) of the study patches over the years 1994 to 2005.Study areas(patches)Study years1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005Patch I – Hograjuli17.7 18.4 20.2 22.6 26.9 19.2 20.6 22.9 22.9 18.2 18.1 21.4Patch II – Foothill19.3 14.3 15.1 5.1 14.3 9.6 5.2 5.8 6.4 19.5 49.2 44.4Patch III – Bengenajuli21.6 20.6 19.0 18.9 12.2 10.9 15.3 20.9 20.2 25.2 29.1 34.8Patch IV – Ramnathpur18.3 24.9 13.9 8.9 9.0 7.2 6.7 13.8 15.1 15.0 10.5 14.1Patch V – Chatai9.2 9.5 13.0 9.3 9.2 10.5 12.7 11.4 13.1 9.9 18.1 16.6Patch VI – Charduar22.4 18.0 10.8 2.2 5.5 6.8 28.0 43.9 29.5 33.0 23.0 38.1 82  M.J. Nath  et al.    D  o  w  n   l  o  a   d  e   d   b  y   [   M  a  n  a  s   h   J .   N  a   t   h   ]  a   t   0   1  :   2   4   3   0   J  a  n  u  a  r  y   2   0   1   2
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