Urban climate versus global climate change—what makes the difference for dengue?

Abstract

The expansion in the geographical distribution of vector-borne diseases is a much emphasized consequence of climate change, as are the consequences of urbanization for diseases that are already endemic, which may be even more important for public health. In this paper, we focus on dengue, the most widespread urban vector-borne disease. Largely urban with a tropical/subtropical distribution and vectored by a domesticated mosquito, Aedes aegypti, dengue poses a serious public health threat. Temperature plays a determinant role in dengue epidemic potential, affecting crucial parts of the mosquito and viral life cycles. The urban predilection of the mosquito species will further exacerbate the impact of global temperature change because of the urban heat island effect. Even within a city, temperatures can vary by 10 °C according to urban land use, and diurnal temperature range (DTR) can be even greater. DTR has been shown to contribute significantly to dengue epidemic potential. Unraveling the importance of within-city temperature is as important for dengue as for the negative health consequences of high temperatures that have thus far been emphasized, for example, pollution and heat stroke. Urban and landscape planning designed to mitigate the non-infectious negative effects of temperature should additionally focus on dengue, which is currently spreading worldwide with no signs of respite.

Fine-scale variation in microclimate across an urban landscape shapes variation in mosquito population dynamics and the potential of Aedes albopictus to transmit arboviral disease

“…This is consistent with other studies showing that urban centers can have different temperature [81–83] and precipitation regimes [84–86] than surrounding areas due to significant modifications to the land-surface structure [44] and increases in the production of waste heat [44]. In other systems, these changes have led to shifts in organism phenology (plants [87–89]), life history (e.g.…”

“…In other systems, these changes have led to shifts in organism phenology (plants [87–89]), life history (e.g. insect pests, ants, fruit bats [90–93]), and overwintering behavior (mosquitoes [83]), all of which can have significant implications for vector-borne disease transmission [76, 83]. Further, because our study site (Athens, Georgia) is a relatively small city, the observed effects of land use on fine-scale variation in microclimate could be much larger in more expansive cities with greater temperature differentials between urban cores and surrounding areas (3°C-10°C differential [79, 80, 83]).…”

Dengue Fever-Associated Maculopathy and Panuveitis in Australia

“…Additionally, major ophthalmic complications such as retinal artery occlusion can occur without severe systemic manifestations of dengue fever [9]. Given the recent outbreaks in Australia and that these trends are likely to continue with the increase in global warming and urban development [17, 18], more ophthalmic presentations are likely to occur even into subtropical Australia where Aedes aegypti is prevalent [19]. …”

Zika Virus: What Have We Learnt Since the Start of the Recent Epidemic?

“…The modeling of simulated risk is usually driven by temperature, precipitation, elevation, land cover and modulated by variables as seasonal or year-round abundance and density (population dynamics), vector biting and mortality rates, and extrinsic incubation period (Carlson et al, 2016;Escobar et al, 2016;Messina et al, 2016;Samy et al, 2016;Attaway et al, 2017). However, besides the accuracy and the assumptions of the model itself, some methodological matters require usually in-depth considerations from the mapping to assess the actual risk, as the space and time scale consistency between data and conclusions, accuracy and representativeness of field-collected data, and the particularities at smaller time or spatial scales (Jian et al, 2016;Misslin et al, 2016;Fischer et al, 2017;Li X. et al, 2017). Hence, the Latin America outbreak was explained by 2015'El Niño-Oscillation South' 2015-2015 at continental level, but also at sub-regional level in Brazil it was explained by year to year variability (drought 2013-2015) and decadal variability followed by long-term trends as climate change (warm 2014-2015) (Munoz et al, 2016;Caminade et al, 2017).…”