scholarly journals Climate change and disease risk in the Himalayas

2011 ◽  
Vol 6 (8) ◽  
pp. 7-8 ◽  
Author(s):  
Sahotra Sarkar

A new challenge is unfolding in the Himalayas: a significant increase in the burden of infectious disease, driven by climate change. Vectors are moving beyond their historic ranges to higher elevations; water quality is deteriorating, and the available supply is diminishing. Preventive and ameliorative measures to address these problems require robust quantitative estimates of the size and spatial distribution of disease risk. Once enough data are available, disease risk can be mapped with predictive models so that appropriate policies can be formulated and implemented. Unfortunately, there has been virtually no quantitative epidemiological attention to this region.DOI: http://dx.doi.org/10.3126/hjs.v6i8.4921 Himalayan Journal of Sciences Vol.6 Issue 8 2010 pp.7-8

Science ◽  
2012 ◽  
Vol 336 (6080) ◽  
pp. 418-419 ◽  
Author(s):  
E. Lindgren ◽  
Y. Andersson ◽  
J. E. Suk ◽  
B. Sudre ◽  
J. C. Semenza

Author(s):  
Chelsea J. Weiskerger ◽  
João Brandão ◽  
Warish Ahmed ◽  
Asli Aslan ◽  
Lindsay Avolio ◽  
...  

Humans may be exposed to microbial pathogens at recreational beaches via environmental sources, such as water, sand, and aerosols. Although infectious disease risk from exposure to waterborne pathogens has been an active area of research for decades, sand is a relatively unexplored reservoir of pathogens and fecal indicator bacteria (FIB). Beach sand and water habitats provide unique advantages and challenges to pathogen introduction, growth, and persistence, as well as continuous exchange between habitats. Models of FIB and pathogen fate and transport in sandy beach habitats can help predict the risk of infectious disease from recreational water use, but filling knowledge gaps such as decay rates and potential for microbial growth in beach habitats is necessary for accurate modeling. Climatic variability, whether natural or anthropogenically-induced, adds complexity to predictive modeling, but may increase human exposure to waterborne pathogens via extreme weather events, warming of water bodies and sea level rise in many regions. The popularity of human recreational beach activities, combined with predicted climate change scenarios, could amplify the risk of human exposure to pathogens and related illnesses. Other global change trends such as increased population growth and urbanization are expected to exacerbate contamination events and the predicted impacts of increasing levels of waterborne pathogens on human health. Such changes will alter microbial population dynamics in beach habitats, and will consequently affect the assumptions and relationships used in population models and quantitative microbial risk assessment (QMRA). Here, we discuss the literature on microbial population and transport dynamics in sand-water continuum habitats at beaches, how these dynamics can be modeled, and how climate change and other anthropogenic influences (e.g., land use, urbanization) should be considered when using and developing more holistic, beachshed-based models.


PLoS Biology ◽  
2020 ◽  
Vol 18 (11) ◽  
pp. e3000938
Author(s):  
Jason R. Rohr ◽  
Jeremy M. Cohen

Climate change is expected to have complex effects on infectious diseases, causing some to increase, others to decrease, and many to shift their distributions. There have been several important advances in understanding the role of climate and climate change on wildlife and human infectious disease dynamics over the past several years. This essay examines 3 major areas of advancement, which include improvements to mechanistic disease models, investigations into the importance of climate variability to disease dynamics, and understanding the consequences of thermal mismatches between host and parasites. Applying the new information derived from these advances to climate–disease models and addressing the pressing knowledge gaps that we identify should improve the capacity to predict how climate change will affect disease risk for both wildlife and humans.


2002 ◽  
Vol 33 (5) ◽  
pp. 415-424 ◽  
Author(s):  
Cintia B. Uvo ◽  
Ronny Berndtsson

Climate variability and climate change are of great concern to economists and energy producers as well as environmentalists as both affect the precipitation and temperature in many regions of the world. Among those affected by climate variability is the Scandinavian Peninsula. Particularly, its winter precipitation and temperature are affected by the variations of the so-called North Atlantic Oscillation (NAO). The objective of this paper is to analyze the spatial distribution of the influence of NAO over Scandinavia. This analysis is a first step to establishing a predictive model, driven by a climatic indicator such as NAO, for the available water resources of different regions in Scandinavia. Such a tool would be valuable for predicting potential of hydropower production one or more seasons in advance.


1998 ◽  
Vol 37 (2) ◽  
pp. 177-185 ◽  
Author(s):  
Hany Hassan ◽  
Keisuke Hanaki ◽  
Tomonori Matsuo

Global climate change induced by increased concentrations of greenhouse gases (especially CO2) is expected to include changes in precipitation, wind speed, incoming solar radiation, and air temperature. These major climate variables directly influence water quality in lakes by altering changes in flow and water temperature balance. High concentration of nutrient enrichment and expected variability of climate can lead to periodic phytoplankton blooms and an alteration of the neutral trophic balance. As a result, dissolved oxygen levels, with low concentrations, can fluctuate widely and algal productivity may reach critical levels. In this work, we will present: 1) recent results of GCMs climate scenarios downscaling project that was held at the University of Derby, UK.; 2) current/future comparative results of a new mathematical lake eutrophication model (LEM) in which output of phytoplankton growth rate and dissolved oxygen will be presented for Suwa lake in Japan as a case study. The model parameters were calibrated for the period of 1973–1983 and validated for the period of 1983–1993. Meterologic, hydrologic, and lake water quality data of 1990 were selected for the assessment analysis. Statistical relationships between seven daily meteorological time series and three airflow indices were used as a means for downscaling daily outputs of Hadley Centre Climate Model (HadCM2SUL) to the station sub-grid scale.


2018 ◽  
Author(s):  
Carmen Longo ◽  
◽  
Elizabeth Balgord ◽  
Timothy F. Diedesch ◽  
John All

2021 ◽  
Vol 713 (1) ◽  
pp. 012011
Author(s):  
A Mirandha ◽  
Irvan ◽  
H Wahyuningsih

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