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It’s complicated: the relationship between climate change and infectious diseases

11 Dec 2009

Patrick Adams

Source: TropIKA.net

 

Global climate change, including increasing sea surface temperatures, increasingly severe weather events, declining air quality and reduced rainfall, is expected to have a significant impact on human health for decades to come. Among the principal concerns associated with climate change is the projected increase in the distribution and prevalence of infectious diseases, mainly through changes in the patterns of pests, parasites and pathogens and alterations to ecosystem composition (1-4).

The World Health Organization has recently devoted attention to the development of early warning systems (EWS) to improve preparedness for, and response to, epidemics (5). The effort draws on recent advances in forecasting weather and climate and improved understanding of interactions between weather and disease, particularly with regard to the impact of climatic variables on disease vectors. Indeed, factors such as temperature, humidity and rainfall have a well-documented affect on the abundance and distribution of insect vectors, playing a role in metabolic activity, egg production and feeding behaviour, among other processes and events.

But exactly how, and to what extent, the climate affects infectious diseases is far from being a settled matter. “Complexity,” write Frumkin and McMichael (6), “is a cardinal feature of climate change,” which they call “an environmental health hazard of unprecedented scale.” Characterized by feedback loops and reciprocal effects, tipping points and surprises, legacy effects and time lags and heterogeneity across time and space, complex systems like climate change elude easy answers or straightforward solutions.

Nor is it clear that climate change is even the most important set of factors affecting infectious diseases. As Lafferty observes in Ecology (7), although the Earth is significantly warmer than it was a century ago, “there is little evidence that climate change has already favored infectious diseases”. He notes that while initial projections suggested dramatic future increases in the geographic range of infectious diseases, “recent models predict range shifts in disease distributions, with little net increase in area”.

The challenge, writes Rohani (8), commenting on a recent study of multi-year climate variability and dengue (9), “is to tease apart the relative impacts of mechanisms that are intrinsic to the host-pathogen interaction (such as human demography and immune-mediated serotype interactions) and climatic drivers such as the El Niño Southern Oscillation (ENSO)”. That study, a set of statistical time-series analyses of the relationship between climate change and dengue transmission in Thailand, Mexico and Puerto Rico, revealed no systematic association between ENSO and multi-annual outbreaks. ENSO’s role, write the authors, “may be obscured by local climate heterogeneity, insufficient data, randomly coincident outbreaks, and other, potentially stronger, intrinsic factors”.

Meanwhile, Taiwanese researchers (13) studying the same relationship found that the strength of ENSO “was consistently a predictor for the occurrence of dengue epidemics” in two geographically diverse regions of Thailand. The authors analyzed global ENSO records, dengue surveillance data, and local meteorological data using Poisson autoregressive models for incidence of cases. Twenty-two percent (in northern provinces) and 15% (in southern provinces) of the variation in the monthly incidence of dengue cases were attributable to global ENSO cycles, and the multivariate ENSO index was an independent predictor in 10 of the 13 studied provinces. Based on their findings, the authors recommend “the effects of ENSO be taken into account in future epidemic forecasting for public health preparedness”.

Several other recent studies looking at the relationship between climate change and dengue epidemics also point to an association between the two. One study from Brazil (11) found that between 1986 and 2003, temperatures in Rio de Janeiro were significantly higher in the years when dengue epidemics broke out than in the years when there were no dengue epidemics. In Taiwan, 2007 saw a two-wave dengue outbreak with dengue incidence exceeding the combined total of the previous four years. According to researchers from China Medical University in Taichung (12), the two-wave outbreak was probably the result of two typhoons. The authors suggest that Taiwan’s increasingly frequent large summer dengue outbreaks, which often persist deep into winter, are “perhaps due to warmer autumns”.

The indirect effects of climate change could lead to an expansion of the range of the dengue vector Aedes aegypti in arid southeast Australia, reports a new study (13) from the University of Queensland. In response to the current and forecasted drying – a result of reduced rainfall – local governments have encouraged the installation of large domestic water tanks in towns and cities in an effort to mitigate the stress on the domestic water supply. The authors predict that this human adaptation to climate change will increase the risk of dengue transmission throughout the region, allowing for the potential re-establishment of Aedes aegypti in New South Wales and the re-emergence of dengue virus.

That geographical expansion is in keeping with global trends. Recent decades have witnessed an alarming increase in the range and severity of dengue epidemics, with the virus now considered endemic in more than 100 countries. WHO estimates that close to half of the world’s population is at risk of dengue infection and that as many as 50 million people are infected globally. Understanding the forces, climatic and otherwise, driving this trend is clearly imperative for global health.

Equally important, and similarly murky, are the effects of climatic factors on the dynamics and distribution of malaria. While climate clearly exerts a strong influence on malaria vectors, that influence may be amplified or negated by a host of socio-economic, environmental and behavioural factors. Examining that relationship, Paaijmans Read and Thomas (9) discuss the critical role of the extrinsic incubation period (EIP) of the parasite in the mosquito. The extremely temperature-sensitive EIP is one of a range of entomological and epidemiological parameters used to determine the basic reproductive number (R0), which defines the number of cases of disease that arise from one case introduced into a susceptible population. The authors report that:

“For P. falciparum, the relationship between ambient temperature (T) and the EIP is approximated by EIP = 111/(T-16), describing the iconic Detinova curve. Use of this equation is ubiquitous, with the vast majority of studies deriving EIP using measures of average monthly temperature to predict current malaria risk, and hence identifying priority areas for allocation of resources for disease control and to assess the impact of climate change on global malaria burdens. However, mosquitoes and the developing malaria parasites do not experience ‘average temperatures,’ but are exposed to temperatures that fluctuate throughout the day … We highlight how diurnal temperature fluctuation has the potential to dramatically alter the rate of development and hence malaria transmission.”

The authors conclude that small changes in EIP due to temperature fluctuation can have a large relative effect on (R0), and thus models based on the Detinova curve may be significantly under-estimating and over-estimating transmission intensity under cool and warm conditions, respectively.

Moreover, beyond helping to explain the presence of malaria under cool conditions, the authors report that the role of temperature fluctuations appear critical to accurately assessing the consequences of climate change: “The influence of short-term fluctuation suggests an important but largely unexplored mechanism via which environmental temperature can affect disease transmission. This adds a layer of complexity to the potential influence of climate change on dynamics of vector borne diseases such as malaria”.

That complexity is echoed in the findings of another study from Kenya (15) by researchers at the Liverpool School of Tropical Medicine (LSTM). Investigating the environmental factors associated with Anopheles gambiae and Anopheles funestus, the primary vectors of P. falciparum in sub-Saharan Africa, they examined the relationship between transmission and environmental measures using bivariate correlations and by comparing environmental means between locations of high and low clustering. Results indicate that the abundance, distribution and transmission patterns of different vectors are driven by different environmental factors (precipitation, temperature, humidity, elevation, and vegetation). Only through improved understanding of the specific ecological parameters of each species, write the authors, can predictions of the effects of climate change on the different malaria vectors be made with any accuracy.

References

1. Haines A, Patz JA (2004). Health effects of climate change. JAMA; 291:99-103. Available from: http://www.ncbi.nlm.nih.gov/pubmed/14709582

2. Patz JA, Campbell-Lendrum D, Holloway T, Foley JA (2005). Impact of regional climate change on human health. Nature; 438:310-317. Available from: http://www.ncbi.nlm.nih.gov/pubmed/16292302

3. Patz JA, Olson SH (2006). Climate change and health: global to local influences on disease risk. Annals of Tropical Medicine and Parasitology; 100:535-549. Available from: http://www.ncbi.nlm.nih.gov/pubmed/16899153

4. McMichael AJ, Woodruff RE, Hales S (2006). Climate change and human health: present and future risks. Lancet; 367:859-869. Available from: http://www.ncbi.nlm.nih.gov/pubmed/16530580

5. World Health Organization (2005). Using climate to predict infectious disease epidemics. Geneva: World Health Organization. Available from: http://www.who.int/globalchange/publications/infectdiseases/en/index.html

6. Frumkin H, McMichael AJ (2008). Climate change and public health: Thinking, communicating, acting. American Journal of Preventive Medicine 35(5): 403-410. Available from: http://www.ncbi.nlm.nih.gov/pubmed/18929964

7. Lafferty KD (2009). The ecology of climate change and infectious diseases. Ecology; 90(4):888-900. Available from: http://www.ncbi.nlm.nih.gov/pubmed/19449681

8. Rohani P (2009). The link between dengue incidence and El Niño Southern Oscillation. PLoS Med 6(11): e1000185. Available from: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2770118/

9. Johansson MA, Cummings DAT, Glass GE (2009). Multiyear climate variability and dengue – El Niño Southern Oscillation, weather, and dengue incidence in Puerto Rico, Mexico, and Thailand: A longitudinal data analysis. PLoS Med 6(11): e10001685. Available from: http://www.ncbi.nlm.nih.gov/pubmed/19918363

10. Tipayamongkholgul M, Fang CT, Klinchan S, Liu CM, King CC (2009). Effects of the El Niño-southern oscillation on dengue epidemics in Thailand, 1996-2005. BMC Public Health 9:422. Available from: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2785791/

11. Câmara FP, Gomes AF, Santos GT, Câmara DC (2009). Climate and dengue epidemics in State of Rio de Janeiro. Revista da Sociedade Brasileira de Medicina Tropical 42(2):137-140. Available from: http://www.ncbi.nlm.nih.gov/pubmed/19448929

12. Hsieh YH, Chen CW (2009). Turning points, reproduction number, and impact of climatological events for multi-wave dengue outbreaks. Tropical Medicine and International Health 14(6): 628-638. Available from: http://www.ncbi.nlm.nih.gov/pubmed/19392743

13. Beebe NW, Cooper RD, Mottram P, Sweeney AW (2009). Australia’s Dengue Risk Driven by Human Adaptation to Climate Change. PLoS Negl Trop Dis; 3(5):e429. Available from:http://www.ncbi.nlm.nih.gov/pubmed/19415109

14 Paaijmans KP, Read AF, Thomas MB (2009). Understanding the link between malaria risk and climate. Proceedings of the National Academy of Sciences 106(33):13844-13849. Available from: http://www.ncbi.nlm.nih.gov/pubmed/19666598

15. Kelly-Hope LA, Hemingway J, McKenzie FE (2009). Environmental factors associated with the malaria vectors Anopheles gambiae and Anopheles funestus in Kenya. Malaria Journal 8(1): 268. Available from: http://www.ncbi.nlm.nih.gov/pubmed/19941637

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