Indicators for climate change-driven urban health impact assessment.

Climate change can cause multiply potential health issues in urban areas, which is the most susceptible environment in terms of the presently increasing climate volatility. Urban greening strategies make an important part of the adaptation strategies which can ameliorate the negative impacts of climate change. It was aimed to study the potential impacts of different kinds of greenings against the adverse effects of climate change, including waterborne, vector-borne diseases, heat-related mortality, and surface ozone concentration in a medium-sized Hungarian city. As greening strategies, large and pocket parks were considered, based on our novel location identifier algorithm for climate risk minimization. A method based on publicly available data sources including satellite pictures, climate scenarios and urban macrostructure has been developed to evaluate the health-related indicator patterns in cities. The modelled future- and current patterns of the indicators have been compared. The results can help the understanding of the possible future state of the studied indicators and the development of adequate greening strategies. Another outcome of the study is that it is not the type of health indicator but its climate sensitivity that determines the extent to which it responds to temperature rises and how effective greening strategies are in addressing the expected problem posed by the factor.

Identification of sampling points for the detection of SARS-CoV-2 in the sewage system.

A suitable tool for monitoring the spread of SARS-CoV-2 is to identify potential sampling points in the wastewater collection system that can be used to monitor the distribution of COVID-19 disease affected clusters within a city. The applicability of the developed methodology is presented through the description of the 72,837 population equivalent wastewater collection system of the city of Nagykanizsa, Hungary and the results of the analytical and epidemiological measurements of the wastewater samples. The wastewater sampling was conducted during the 3rd wave of the COVID-19 epidemic. It was found that the overlap between the road system and the wastewater network is high, it is 82 %. It was showed that the proposed methodological approach, using the tools of network science, determines confidently the zones of the wastewater collection system and provides the ideal monitoring points in order to provide the best sampling resolution in urban areas. The strength of the presented approach is that it estimates the network based on publicly available information. It was concluded that the number of zones or sampling points can be chosen based on relevant epidemiological intervention and mitigation strategies. The algorithm allows for continuous effective monitoring of the population infected by SARS-CoV-2 in small-sized cities.

The potential impact of climate change on the seasonality of Phlebotomus neglectus, the vector of visceral leishmaniasis in the East Mediterranean region.

Phlebotomus neglectus is one of the most important vectors of visceral leishmaniasis in Southeast Europe and Asia Minor. It was aimed to study the impact of climate change on the seasonality and the range of the species for 2014-2060. In the inland areas of Asia Minor, the Balkan Peninsula and the Carpathian Basin the elongation of the activity season will reach or exceed the two months in the middle of the 21st century compared to the end of the 20th century. The most affected regions are the middle elevations of the mountainous regions and the plains of the northern distribution areas. In some areas of the southern distribution border, the season is expected to shorten. In the Apennine Peninsula, mainly the mountainous areas could be impacted notably by climate change. The results indicate the potential spread of leishmaniasis in Southeast Europe due to the increasing environmental suitability of the region.

Climate change projections for Carpathian soda pans on the basis of photosynthesis evidence from typical diatom species.

The Carpathian Basin is home to a number of astatic soda pans which are especially vulnerable to the climate change due to their high degree of hydrological sensitivity. The photosynthetic plasticity of the three most dominant benthic diatom species (Nitzschia aurariae, N. reskovii, N. supralitorea) in a number of soda pans was measured, along with sulphate and chloride ion content; conductivity and temperature gradients were also recorded. On the basis of the maximal photosynthetic activity (Ps), climate models were employed to observe and predict the effects of climate change on photosynthesis over three time-spans: past (1970-2000), recent past (2005-2015) and projected future (2041-2060). Comparing the periods, it becomes apparent that climate change has a significant effect on photosynthesis and the photosynthetically active period of the Nitzschia species, the dominant primary producers in soda pans, by enhancing their photosynthetic activity and extending their vegetation period by two months. Due to the breadth of their ecological niche, the competitive advantages of the diatom species studied in the course of this research as against others are expected to prevail under the conditions predicted by the climate scenario presented here.

The potential impact of climate change on the transmission risk of tick-borne encephalitis in Hungary.

BACKGROUND: Impact of climate change on tick-borne encephalitis (TBE) prevalence in the tick-host enzootic cycle in a given region depends on how the region-specific climate change patterns influence tick population development processes and tick-borne encephalitis virus (TBEV) transmission dynamics involving both systemic and co-feeding transmission routes. Predicting the transmission risk of TBEV in the enzootic cycle with projected climate conditions is essential for planning public health interventions including vaccination programs to mitigate the TBE incidence in the inhabitants and travelers. We have previously developed and validated a mathematical model for retroactive analysis of weather fluctuation on TBE prevalence in Hungary, and we aim to show in this research that this model provides an effective tool for projecting TBEV transmission risk in the enzootic cycle. METHODS: Using the established model of TBEV transmission and the climate predictions of the Vas county in western Hungary in 2021-2050 and 2071-2100, we quantify the risk of TBEV transmission using a series of summative indices - the basic reproduction number, the duration of infestation, the stage-specific tick densities, and the accumulated (tick) infections due to co-feeding transmission. We also measure the significance of co-feeding transmission by observing the cumulative number of new transmissions through the non-systemic transmission route. RESULTS: The transmission potential and the risk in the study site are expected to increase along with the increase of the temperature in 2021-2050 and 2071-2100. This increase will be facilitated by the expected extension of the tick questing season and the increase of the numbers of susceptible ticks (larval and nymphal) and the number of infected nymphal ticks co-feeding on the same hosts, leading to compounded increase of infections through the non-systemic transmission. CONCLUSIONS: The developed mathematical model provides an effective tool for predicting TBE prevalence in the tick-host enzootic cycle, by integrating climate projection with emerging knowledge about the region-specific tick ecological and pathogen enzootic processes (through model parametrization fitting to historical data). Model projects increasing co-feeding transmission and prevalence of TBEV in a recognized TBE endemic region, so human risk of TBEV infection is likely increasing unless public health interventions are enhanced.

Assessing systemic and non-systemic transmission risk of tick-borne encephalitis virus in Hungary.

Estimating the tick-borne encephalitis (TBE) infection risk under substantial uncertainties of the vector abundance, environmental condition and human-tick interaction is important for evidence-informed public health intervention strategies. Estimating this risk is computationally challenging since the data we observe, i.e., the human incidence of TBE, is only the final outcome of the tick-host transmission and tick-human contact processes. The challenge also increases since the complex TBE virus (TBEV) transmission cycle involves the non-systemic route of transmission between co-feeding ticks. Here, we describe the hidden Markov transition process, using a novel TBEV transmission-human case reporting cascade model that couples the susceptible-infected compartmental model describing the TBEV transmission dynamics among ticks, animal hosts and humans, with the stochastic observation process of human TBE reporting given infection. By fitting human incidence data in Hungary to the transmission model, we estimate key parameters relevant to the tick-host interaction and tick-human transmission. We then use the parametrized cascade model to assess the transmission potential of TBEV in the enzootic cycle with respect to the climate change, and to evaluate the contribution of non-systemic transmission. We show that the TBEV transmission potential in the enzootic cycle has been increasing along with the increased temperature though the TBE human incidence has dropped since 1990s, emphasizing the importance of persistent public health interventions. By demonstrating that non-systemic transmission pathway is a significant factor in the transmission of TBEV in Hungary, we conclude that the risk of TBE infection will be highly underestimated if the non-systemic transmission route is neglected in the risk assessment.

Exploration of the heterogeneous effect of climate change on ozone concentration in an urban environment.

Ozone is a significant causative agent of mortality in cities. Urban environments are expressly vulnerable to global warming because of the extensive emission of air pollutants with urban heat island effect enhancing much rapidly the ozone concentration than in the less urbanized regions. This effect previously was not studied in local scale. It was hypothesized that climate change will cause heterogenic increase of ozone concentration in the different parts of the cities. To study this effect, the near-surface ozone concentration of 10 points of a Hungarian city was measured and modeled. At first step, the local correlations between solar radiation, air temperature, relative humidity and the near surface ozone concentrations at 3 m height were determined, specifying the local ozone-producing conditions. Then, based on the scenario of the Intergovernmental Panel on Climate Change 5th assessment report, the future seasonal near-surface ozone concentrations were modeled. Based on the model, it was determined that climate change will result in a heterogenic increase of near-surface ozone concentration.