Sensitivity of vegetation to climate variability and its implications for malaria risk in Baringo, Kenya

The global increase in vector borne diseases has been linked to climate change. Seasonal vegetation changes are known to influence disease vector population. However, the relationship is more theoretical than quantitatively defined. There is a growing demand for understanding and prediction of climate sensitive vector borne disease risks especially in regions where meteorological data are lacking. This study aimed at analyzing and quantitatively assessing the seasonal and year-to-year association between climatic factors (rainfall and temperature) and vegetation cover, and its implications for malaria risks in Baringo County, Kenya. Remotely sensed temperature, rainfall, and vegetation data for the period 2004–2015 were used. Poisson regression was used to model the association between malaria cases and climatic and environmental factors for the period 2009–2012, this being the period for which all datasets overlapped. A strong positive relationship was observed between the Normalized Difference Vegetation Index (NDVI) and monthly total precipitation. There was a strong negative relationship between NDVI and minimum temperature. The total monthly rainfall (between 94 -181mm), average monthly minimum temperatures (between 16–21°C) and mean monthly NDVI values lower than 0.35 were significantly associated with malaria incidence rates. Results suggests that a combination of climatic and vegetation greenness thresholds need to be met for malaria incidence to be significantly increased in the county. Planning for malaria control can therefore be enhanced by incorporating these factors in malaria risk mapping.

[1]  Craig Stoops,et al.  President's Malaria Initiative , 2008 .

[2]  Kenya.,et al.  2010 Kenya Malaria Indicator Survey , 2011 .

[3]  L. Haugh.  Checking the Independence of Two Covariance-Stationary Time Series: A Univariate Residual Cross-Correlation Approach , 1976 .

[4]  B. Lyon,et al.  Unraveling East Africa's Climate Paradox , 2017 .

[5]  J. Carpenter,et al.  Practice of Epidemiology Comparison of Random Forest and Parametric Imputation Models for Imputing Missing Data Using MICE: A CALIBER Study , 2014 .

[6]  P. Good,et al.  Reconciling Past and Future Rainfall Trends over East Africa , 2014 .

[7]  R. Andimuthu,et al.  Spatial trend, environmental and socioeconomic factors associated with malaria prevalence in Chennai , 2014, Malaria Journal.

[8]  Carlos A. Coelho,et al.  Projected Changes in Mean and Extreme Precipitation in Africa under Global Warming. Part I: Southern Africa , 2009 .

[9]  Kenya..  Kenya Malaria Indicator Survey 2015 , 2016 .

[10]  Joacim Rocklöv,et al.  Remotely Sensed Environmental Conditions and Malaria Mortality in Three Malaria Endemic Regions in Western Kenya , 2016, PloS one.

[11]  Ed Hawkins,et al.  Making sense of the early-2000s warming slowdown , 2016 .

[12]  R. Cibulskis,et al.  World Malaria Report 2013 , 2014 .

[13]  C. Tucker,et al.  Coupled vegetation‐precipitation variability observed from satellite and climate records , 2003 .

[14]  J. Beier,et al.  The invasive shrub Prosopis juliflora enhances the malaria parasite transmission capacity of Anopheles mosquitoes: a habitat manipulation experiment , 2017, Malaria Journal.

[15]  S. Shankar,et al.  Role of geospatial technology in identifying natural habitat of malarial vectors in South Andaman, India. , 2016, Journal of vector borne diseases.

[16]  A. Viña,et al.  Drought Monitoring with NDVI-Based Standardized Vegetation Index , 2002 .

[17]  E. Forootan,et al.  Changes in temperature and precipitation extremes over the Greater Horn of Africa region from 1961 to 2010 , 2014 .

[18]  L. Ogallo,et al.  Recent Trends of Minimum and Maximum Surface Temperatures over Eastern Africa , 2000 .

[19]  A. Githeko,et al.  Vulnerability to epidemic malaria in the highlands of Lake Victoria basin: the role of climate change/variability, hydrology and socio-economic factors , 2010 .

[20]  Variability of maximum and mean average temperature across Libya (1945–2009) , 2014, Theoretical and Applied Climatology.

[21]  Tobias Landmann,et al.  Spatial analysis of human-induced vegetation productivity decline over eastern Africa using a decade (2001-2011) of medium resolution MODIS time-series data , 2014, Int. J. Appl. Earth Obs. Geoinformation.

[22]  E.,et al.  Projected Changes in Mean and Extreme Precipitation in Africa under Global Warming. Part II: East Africa , 2009 .

[23]  A. Anyamba,et al.  Species composition, larval habitats, seasonal occurrence and distribution of potential malaria vectors and associated species of Anopheles (Diptera: Culicidae) from the Republic of Korea , 2010, Malaria Journal.

[24]  Shilu Tong,et al.  Climatic variables and transmission of malaria: a 12-year data analysis in Shuchen County, China. , 2003, Public health reports.

[25]  C. Reason,et al.  Contributions of Indian Ocean Sea Surface Temperatures to Enhanced East African Rainfall , 2009 .

[26]  John E. Kutzbach,et al.  Assessing Global Vegetation–Climate Feedbacks from Observations* , 2006 .

[27]  Masahiro Hashizume,et al.  The Indian Ocean Dipole and malaria risk in the highlands of western Kenya , 2009, Proceedings of the National Academy of Sciences.

[28]  B. Sartorius,et al.  Clinical Malaria Transmission Trends and Its Association with Climatic Variables in Tubu Village, Botswana: A Retrospective Analysis , 2016, PloS one.

[29]  U. Haque,et al.  The Role of Climate Variability in the Spread of Malaria in Bangladeshi Highlands , 2010, PloS one.

[30]  Thomas A. Smith,et al.  Incidence and admission rates for severe malaria and their impact on mortality in Africa , 2017, Malaria Journal.

[31]  Willem Takken,et al.  Relevant microclimate for determining the development rate of malaria mosquitoes and possible implications of climate change , 2010, Malaria Journal.

[32]  S. Schneider,et al.  Climate Change 2001: Synthesis Report: A contribution of Working Groups I, II, and III to the Third Assessment Report of the Intergovernmental Panel on Climate Change , 2001 .

[33]  S. Tong,et al.  Climatic Variables and Transmission of Malaria: A 12-Year Data Analysis in Shuchen County, China , 2003, Public health reports.

[34]  K. Paaijmans,et al.  Optimal temperature for malaria transmission is dramatically lower than previously predicted. , 2013, Ecology letters.

[35]  A. Githeko,et al.  Development and validation of climate and ecosystem-based early malaria epidemic prediction models in East Africa , 2014, Malaria Journal.

[36]  V. Louis,et al.  Effect of meteorological factors on clinical malaria risk among children: an assessment using village-based meteorological stations and community-based parasitological survey , 2007, BMC public health.

[37]  Alemayehu Midekisa,et al.  Remote sensing-based time series models for malaria early warning in the highlands of Ethiopia , 2012, Malaria Journal.

[38]  Roger Jones,et al.  Regional climate projections , 2007 .

[39]  G. Yan,et al.  The Effects of Climatic Factors on the Distribution and Abundance of Malaria Vectors in Kenya , 2002, Journal of medical entomology.

[40]  S. Hay,et al.  Earth observation, geographic information systems and Plasmodium falciparum malaria in sub-Saharan Africa. , 2000, Advances in parasitology.

[41]  Samuel N. Goward,et al.  Transient Effects of Climate on Vegetation Dynamics: Satellite Observations , 1995 .

[42]  Mark A. Cane,et al.  The East African Long Rains in Observations and Models , 2013 .

[43]  S. Chou,et al.  Long-term Temperature and Rainfall Trends over Northeast Brazil and Cape Verde , 2015 .

[44]  Chris Funk,et al.  Mapping recent decadal climate variations in precipitation and temperature across eastern Africa and the Sahel , 2012 .

[45]  Masimalai Palaniyandi,et al.  Environmental risk factors in relation to occurrence of vector borne disease epidemics: Remote sensing and GIS for rapid assessment, picturesque, and monitoring towards sustainable health , 2017 .

[46]  C. Funk,et al.  Climatic trends over Ethiopia: regional signals and drivers , 2013 .

[47]  Catherine Linard,et al.  Mapping intra-urban malaria risk using high resolution satellite imagery: a case study of Dar es Salaam , 2016, International Journal of Health Geographics.

[48]  H. L. Miller,et al.  Climate Change 2007: The Physical Science Basis , 2007 .

[49]  A. Githeko,et al.  Predicting Malaria Epidemics in the Kenyan Highlands Using Climate Data: A Tool for Decision Makers , 2001 .

[50]  Ulrich Kuch,et al.  Spatio-temporal distribution of malaria and its association with climatic factors and vector-control interventions in two high-risk districts of Nepal , 2014, Malaria Journal.

[51]  Else Swinnen,et al.  Vegetation response to precipitation variability in East Africa controlled by biogeographical factors , 2016 .

[52]  Xiaoping Xin,et al.  The implications of serial correlation and time-lag effects for the impact study of climate change on vegetation dynamics – a case study with Hulunber meadow steppe, Inner Mongolia , 2015 .

[53]  M. Hashizume,et al.  A Systematic Review of Methodology: Time Series Regression Analysis for Environmental Factors and Infectious Diseases , 2014, Tropical medicine and health.

[54]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[55]  T. Jaeger,et al.  Categorical Data Analysis: Away from ANOVAs (transformation or not) and towards Logit Mixed Models. , 2008, Journal of memory and language.

[56]  M. Hoerling,et al.  Understanding Recent Eastern Horn of Africa Rainfall Variability and Change , 2014 .