scholarly journals Identification of bio-climatic determinants and potential risk areas for Kyasanur forest disease in Southern India using MaxEnt modelling approach

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Malay Pramanik ◽  
Poonam Singh ◽  
Ramesh C. Dhiman
Keyword(s):  
Tamil Nadu ◽  
Climatic Variables ◽  
Southern India ◽  
Forest Disease ◽  
Diurnal Temperature ◽  
Mean Temperature ◽  
Bioclimatic Variables ◽  
The Mean ◽  
Kyasanur Forest Disease ◽  
Modelling Approach

Abstract Background Kyasanur forest disease (KFD), known as monkey fever, was for the first time reported in 1957 from the Shivamogga district of Karnataka. But since 2011, it has been spreading to the neighbouring state of Kerala, Goa, Maharashtra, and Tamil Nadu. The disease is transmitted to humans, monkeys and by the infected bite of ticks Haemaphysalis spinigera. It is known that deforestation and ecological changes are the main reasons for KFD emergence, but the bio-climatic understanding and emerging pathways remain unknown. Methods The present study aims to understand the bio-climatic determinants of distribution of tick vector of KFD in southern India using the Maximum Entropy (MaxEnt) model. The analysis was done using 34 locations of Haemaphysalis spinigera occurrence and nineteen bio-climatic variables from WorldClim. Climatic variables contribution was assessed using the Jackknife test and mean AUC 0.859, indicating the model performs with very high accuracy. Results Most influential variables affecting the spatial distribution of Haemaphysalis spinigera were the average temperature of the warmest quarter (bio10, contributed 32.5%), average diurnal temperature range (bio2, contributed 21%), precipitation of wettest period (bio13, contributed 17.6%), and annual precipitation (bio12, contributed 11.1%). The highest probability of Haemaphysalis spinigera presence was found when the mean warmest quarter temperature ranged between 25.4 and 30 °C. The risk of availability of the tick increased noticeably when the mean diurnal temperature ranged between 8 and 10 °C. The tick also preferred habitat having an annual mean temperature (bio1) between 23 and 26.2 °C, mean temperature of the driest quarter (bio9) between 20 and 28 °C, and mean temperature of the wettest quarter (bio8) between 22.5 and 25 °C. Conclusions The results have established the relationship between bioclimatic variables and KFD tick distribution and mapped the potential areas for KFD in adjacent areas wherein surveillance for the disease is warranted for early preparedness before the occurrence of outbreaks etc. The modelling approach helps link bio-climatic variables with the present and predicted distribution of Haemaphysalis spinigera tick.

Identification of Bio-climatic Determinants and Potential Risk Areas for Kyasanur Forest Disease in Southern India using MaxEnt Modelling Approach

2020 ◽  
Author(s):  
Malay Kumar Pramanik ◽  
Poonam Singh ◽  
Ramesh C Dhiman
Keyword(s):  
Tamil Nadu ◽  
Climatic Variables ◽  
Southern India ◽  
Forest Disease ◽  
Diurnal Temperature ◽  
Mean Temperature ◽  
Bioclimatic Variables ◽  
Tick Distribution ◽  
Kyasanur Forest Disease ◽  
Modelling Approach

Abstract Background: Kyasanur Forest Disease (KFD), known as monkey fever was for the first time reported in 1957 from Shivamogga district of Karnataka. But since 2011, it is spreading to the neighbouring state of Kerala, Goa, Maharashtra, and Tamil Nadu. The disease is transmitted to humans, monkeys and by the infected bite of ticks Haemaphysalis spinigera. It is known that deforestation and ecological changes are the main reasons for KFD emergence, but the bio-climatic understanding and emerging pathways remain unknown.Methods: The present study aims to understand the bio-climatic determinants of KFD tick distribution in southern India using Maximum Entropy (MaxEnt) model. The analysis was done using 34 locations of Haemaphysalis spinigera occurrence and nineteen bio-climatic variables from WorldClim. Climatic variables’ contribution was assessed using the jackknife test and mean AUC 0.859 which indicated the model performs with very high accuracy.Results: Most influential variables affecting the spatial distribution of Haemaphysalis spinigera were the average temperature of the warmest quarter (bio10, contributed 32.5%), average diurnal temperature range (bio2, contributed 21%), precipitation of wettest period (bio13, contributed 17.6%), and annual precipitation (bio12, contributed 11.1%). The highest probability of Haemaphysalis spinigera presence was found when mean warmest quarter temperature ranged between 25.4-30°C. The risk of availability of the tick increases noticeably when the mean diurnal temperature ranged between 8-10°C. The tick also preferred habitat having an annual mean temperature (bio1) between 23-26.2°C, mean temperature of the driest quarter (bio9) between 20-28°C, and mean temperature of the wettest quarter (bio8) between 22.5-25°C.Conclusions: The results have established the relationship between bioclimatic variables and KFD tick distribution and mapped the potential areas for KFD in adjacent areas wherein surveillance for the disease is warranted for early preparedness before the occurrence of outbreaks etc. The modelling approach has been found a very useful tool to link bioclimatic variables with present and predicted distribution of Haemaphysalis spinigera tick .

scholarly journals Modelling Climate Suitability for Rainfed Maize Cultivation in Kenya Using a Maximum Entropy (MaxENT) Approach

Agronomy ◽  
2019 ◽  
Vol 9 (11) ◽  
pp. 727 ◽  
Author(s):  
Benjamin Kipkemboi Kogo ◽  
Lalit Kumar ◽  
Richard Koech ◽  
Champika S. Kariyawasam
Keyword(s):  
Maximum Entropy ◽  
General Circulation ◽  
General Circulation Models ◽  
Mitigation Strategies ◽  
Maize Production ◽  
Maxent Model ◽  
Mean Temperature ◽  
Bioclimatic Variables ◽  
Climatic Scenarios ◽  
The Mean

Climate change and variability are projected to alter the geographic suitability of lands for crop cultivation. In many developing countries, such as Kenya, information on the mean changes in climate is limited. Therefore, in this study, we model the current and future changes in areas suitable for rainfed maize production in the country using a maximum entropy (MaxENT) model. Maize is by far a major staple food crop in Kenya. We used maize occurrence location data and bioclimatic variables for two climatic scenarios-Representative Concentration Pathways (RCP) 4.5 and 8.5 from two general circulation models (HadGEM2-ES and CCSM4) for 2070. The study identified the annual mean temperature, annual precipitation and the mean temperature of the wettest quarter as the major variables that affect the distribution of maize. Simulation results indicate an average increase of unsuitable areas of between 1.9–3.9% and a decrease of moderately suitable areas of 14.6–17.5%. The change in the suitable areas is an increase of between 17–20% and in highly suitable areas of 9.6% under the climatic scenarios. The findings of this study are of utmost importance to the country as they present an opportunity for policy makers to develop appropriate adaptation and mitigation strategies required to sustain maize production under future climates.

scholarly journals The Sankara Nethralaya Tamil Nadu Essilor Myopia (STEM) Study—Defining a Threshold for Non-Cycloplegic Myopia Prevalence in Children

2021 ◽  
Vol 10 (6) ◽  
pp. 1215
Author(s):  
Aparna Gopalakrishnan ◽  
Jameel Rizwana Hussaindeen ◽  
Viswanathan Sivaraman ◽  
Meenakshi Swaminathan ◽  
Yee Ling Wong ◽  
...  
Keyword(s):  
Open Field ◽  
Tamil Nadu ◽  
Mean Difference ◽  
School Vision ◽  
Elite School ◽  
Prevalence Estimates ◽  
The Mean ◽  
Clinically Significant ◽  
Set Up ◽  
Definition Of

The aim of this study was to investigate the agreement between cycloplegic and non-cycloplegic autorefraction with an open-field auto refractor in a school vision screening set up, and to define a threshold for myopia that agrees with the standard cycloplegic refraction threshold. The study was conducted as part of the Sankara Nethralaya Tamil Nadu Essilor Myopia (STEM) study, which investigated the prevalence, incidence, and risk factors for myopia among children in South India. Children from two schools aged 5 to 15 years, with no ocular abnormalities and whose parents gave informed consent for cycloplegic refraction were included in the study. All the children underwent visual acuity assessment (Pocket Vision Screener, Elite school of Optometry, India), followed by non-cycloplegic and cycloplegic (1% tropicamide) open-field autorefraction (Grand Seiko, WAM-5500). A total of 387 children were included in the study, of whom 201 were boys. The mean (SD) age of the children was 12.2 (±2.1) years. Overall, the mean difference between cycloplegic and non-cycloplegic spherical equivalent (SE) open-field autorefraction measures was 0.34 D (limits of agreement (LOA), 1.06 D to −0.38 D). For myopes, the mean difference between cycloplegic and non-cycloplegic SE was 0.13 D (LOA, 0.63D to −0.36D). The prevalence of myopia was 12% (95% CI, 8% to 15%) using the threshold of cycloplegic SE ≤ −0.50 D, and was 14% (95% CI, 11% to 17%) with SE ≤ −0.50 D using non-cycloplegic refraction. When myopia was defined as SE of ≤−0.75 D under non-cycloplegic conditions, there was no difference between cycloplegic and non-cycloplegic open-field autorefraction prevalence estimates (12%; 95% CI, 8% to 15%; p = 1.00). Overall, non-cycloplegic refraction underestimates hyperopia and overestimates myopia; but for subjects with myopia, this difference is minimal and not clinically significant. A threshold of SE ≤ −0.75 D agrees well for the estimation of myopia prevalence among children when using non-cycloplegic refraction and is comparable with the standard definition of cycloplegic myopic refraction of SE ≤ −0.50 D.

scholarly journals Where should police forces target their residential burglary reduction efforts? Using official victimisation data to predict burglary incidences at the neighbourhood level

Crime Science ◽  
2021 ◽  
Vol 10 (1) ◽  
Author(s):  
James Hunter ◽  
Bethany Ward ◽  
Andromachi Tseloni ◽  
Ken Pease
Keyword(s):  
Police Officers ◽  
Crime Rates ◽  
Crime Reduction ◽  
Residential Burglary ◽  
England And Wales ◽  
Neighbourhood Level ◽  
The Mean ◽  
Terrain Modelling ◽  
Modelling Approach ◽  
Police Forces

AbstractExpected crime rates that enable police forces to contrast recorded and anticipated spatial patterns of crime victimisation offer a valuable tool in evaluating the under-reporting of crime and inform/guide crime reduction initiatives. Prior to this study, police forces had no access to expected burglary maps at the neighbourhood level covering all parts of England and Wales. Drawing on analysis of the Crime Survey for England and Wales and employing a population terrain modelling approach, this paper utilises household and area characteristics to predict the mean residential burglary incidences per 1000 population across all neighbourhoods in England and Wales. The analysis identifies distinct differences in recorded and expected neighbourhood burglary incidences at the Output Area level, providing a catalyst for stimulating further reflection by police officers and crime analysts.

scholarly journals Low mammalian species richness is associated with Kyasanur forest disease outbreak risk in deforested landscapes in the Western Ghats, India

One Health ◽  
2021 ◽  
pp. 100299
Author(s):  
Michael G. Walsh ◽  
Rashmi Bhat ◽  
Venkatesh Nagarajan-Radha ◽  
Prakash Narayanan ◽  
Navya Vyas ◽  
...  
Keyword(s):  
Species Richness ◽  
Western Ghats ◽  
Mammalian Species ◽  
Disease Outbreak ◽  
Forest Disease ◽  
Kyasanur Forest Disease ◽  
The Western Ghats

scholarly journals In-silico design of envelope based multi-epitope vaccine candidate against Kyasanur forest disease virus

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Sathishkumar Arumugam ◽  
Prasad Varamballi
Keyword(s):  
Disease Virus ◽  
In Silico ◽  
Hemorrhagic Fever ◽  
Epitope Vaccine ◽  
Epitope Region ◽  
Vaccine Candidates ◽  
Forest Disease ◽  
In Silico Design ◽  
Antigenic Properties ◽  
Kyasanur Forest Disease

AbstractKyasanur forest disease virus (KFDV) causing tick-borne hemorrhagic fever which was earlier endemic to western Ghats, southern India, it is now encroaching into new geographic regions, but there is no approved medicine or effective vaccine against this deadly disease. In this study, we did in-silico design of multi-epitope subunit vaccine for KFDV. B-cell and T-cell epitopes were predicted from conserved regions of KFDV envelope protein and two vaccine candidates (VC1 and VC2) were constructed, those were found to be non-allergic and possess good antigenic properties, also gives cross-protection against Alkhurma hemorrhagic fever virus. The 3D structures of vaccine candidates were built and validated. Docking analysis of vaccine candidates with toll-like receptor-2 (TLR-2) by Cluspro and PatchDock revealed strong affinity between VC1 and TLR2. Ligplot tool was identified the intermolecular hydrogen bonds between vaccine candidates and TLR-2, iMOD server confirmed the stability of the docking complexes. JCAT sever ensured cloning efficiency of both vaccine constructs and in-silico cloning into pET30a (+) vector by SnapGene showed successful translation of epitope region. IMMSIM server was identified increased immunological responses. Finally, multi-epitope vaccine candidates were designed and validated their efficiency, it may pave the way for up-coming vaccine and diagnostic kit development.

scholarly journals Isolation of Kyasanur Forest Disease Virus from Febrile Patient, Yunnan, China

2009 ◽  
Vol 15 (2) ◽  
pp. 326-328 ◽  
Author(s):  
Jinglin Wang ◽  
Hailin Zhang ◽  
Shihong Fu ◽  
Huanyu Wang ◽  
Daxin Ni ◽  
...  
Keyword(s):  
Disease Virus ◽  
Febrile Patient ◽  
Forest Disease ◽  
Kyasanur Forest Disease
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