key: cord-1024749-umonfqdk authors: Balachandra Kumar, V.; Rooney, N. J.; Carr, A. title: Nipah virus from bats - another potential pandemic? Risk mapping the impact of anthropogenic and climate change on the transmission of Nipah virus infection to humans. date: 2022-02-22 journal: nan DOI: 10.1101/2022.02.21.22271216 sha: 05915695c4a03628399433da42a540f6dccbb51a doc_id: 1024749 cord_uid: umonfqdk Henipavirus infection (NiV), a fatal disease transmitted by bats has caused human death and disease in India and Bangladesh. With an average case fatality rate of more than 70%, NiV has the potential to cause widespread outbreaks that can have a devastating impact on human health. Spillover of NiV from bats to humans is influenced by several factors mainly human behaviour and human interaction with bats. Climatic conditions and habitat destruction influence the shedding of the virus and the transmission of the disease to humans. Limited research has been conducted on the factors driving these spillover events. As the world has recently witnessed the devastating impact of the COVID-19 global pandemic, a forewarning of spillover events will enable the adoption of adequate measures to prevent and control future outbreaks. Our study maps the likely changing distribution of NiV reservoir Pteropus medius bat species using future climate and landuse change predictions. We use existing data to predict which districts within India and Bangladesh have increased risk of spillover of NiV in the future. We use Species Distribution Modelling to predict the likely change in the distribution of P. medius under different future scenarios and the concurrent increase in the risk of NiV spillover events. We focus on the influence of anthropogenic changes in different socioeconomic scenarios to predict future spillover events. We consider climate and social goals set by the International Panel on Climate Change (IPPC) to create accurate predictions of regions at risk of NiV spillovers. We find that the risk of NiV spillover events in India and Bangladesh will likely increase. More districts are predicted to be at risk of NiV spillovers under the high population growth and persistent environmental degradation scenario than under moderate population growth and medium challenges to achieve climate goals. This highlights the significance of population growth and climate change when considering disease outbreaks and public health. Our findings will enable the authorities in the predicted spillover regions to take public health measures to prevent and control NiV outbreaks. use change predictions. We use existing data to predict which districts within India and Bangladesh have 23 increased risk of spillover of NiV in the future. We use Species Distribution Modelling to predict the likely 24 change in the distribution of P. medius under different future scenarios and the concurrent increase in the risk 25 of NiV spillover events. We focus on the influence of anthropogenic changes in different socioeconomic 26 scenarios to predict future spillover events. We consider climate and social goals set by the International 27 Panel on Climate Change (IPPC) to create accurate predictions of regions at risk of NiV spillovers. We find 28 that the risk of NiV spillover events in India and Bangladesh will likely increase. More districts are predicted 29 to be at risk of NiV spillovers under the high population growth and persistent environmental degradation 30 scenario than under moderate population growth and medium challenges to achieve climate goals. This 31 highlights the significance of population growth and climate change when considering disease outbreaks and 32 public health. Our findings will enable the authorities in the predicted spillover regions to take public health Coalition for Epidemic Preparedness Innovations (CEPI) has also prioritized NiV for vaccine development [5] . 44 However, our understanding of the dynamics of NiV transmission and its pathology remains vague, as the 45 conditions leading to its transmission have not been consistent across spillover events in different regions. 46 The first human case of NiV was reported in 1998 in Malaysia. The disease was transmitted zoonotically from 47 pigs to farmers who were in direct contact with the affected animals. Thus, pigs acted as an intermediate host 48 in the Malaysian outbreak. The disease spread to Singapore through the import of these infected pigs [6] . In The main difference between the Malaysian and Bangladesh/Indian outbreaks, was the route of transmission. NiV is an RNA virus that can mutate rapidly to adapt to changing conditions. This enables the virus to overcome 64 barriers to its transmission and infectivity [11] . NiV can mutate to infect new host species, thereby increasing 65 the chance of spillover through different domesticated species [12] . Antibodies against NiV have been found 66 in cattle, goats, and pigs in Bangladesh [13] . Even though no zoonotic transmission of the disease through 67 livestock has yet been reported in Bangladesh However, the impact of anthropogenic changes has not been adequately considered in predicting future 106 outbreaks. Our study aims to predict areas susceptible to spillovers in the future, by considering likely land- CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted February 22, 2022. ; https://doi.org/10.1101/2022.02.21.22271216 doi: medRxiv preprint technology. SSP1, the lowest emission scenario, follows the path of sustainability, with few challenges to 111 achieving climate and socioeconomic goals. SSP2 is a 'middle of the road' scenario with moderate 112 population growth and medium challenges to achieve climate goals. SSP3 predicts high population growth in 113 developing countries and persistent environmental degradation with strong challenges to achieving climate 114 goals. SSP4, the 'worst-case scenario' is characterised by high social disparity, poor technological 115 development, and failure to achieve climate and socioeconomic goals. We use Species Distribution were included in this study to generate a current distribution model of the species. . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted February 22, 2022. ; https://doi.org/10.1101/2022.02.21.22271216 doi: medRxiv preprint Spatial data for 130 layers was initially collected from several databases for current and future scenarios. The CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) presence data was used to determine the statistical significance of each model. Generating categorical maps 177 We created categorical distribution maps using district boundaries within India and Bangladesh. We inferred Human modification of land ( Fig. S2-a) seems to increase the suitability for the species whereas the effect of 201 population density (Fig S2-b) stabilizes after a rapid rise. The distribution also seems to increase initially with 202 an increase in annual PET (Fig S2-c) , peaks and then decreases. Increasing continentality (Fig S2-d for the 10 th percentile training presence is <0.01. The highest contributor is the urban land layer with a 207 contribution of 33.7%, followed by temperature seasonality (13.8%), and pastureland (11.5%). Other variables 208 have a contribution of less than 10%. Jackknife analysis shows that urban land cover is the most important 209 variable with model performance decreasing considerably when the layer is removed (Fig S1-b) . Models for 210 the two GCMs show mostly similar predictions. Across all four scenarios, the future projections predict a 211 . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted February 22, 2022. ; https://doi.org/10.1101/2022.02.21.22271216 doi: medRxiv preprint Northward shift from the Southern states where the species is predicted to be more prevalent according to the 212 current model. 213 Increase in urban land cover (Fig. 4-a) increases the suitability of the land for the species whereas increase in 214 pastureland ( Fig. 4-b) decreases suitability of the land. Increasing annual mean temperature (Fig. 4-c) up to 215 25 o C seems favourable for the bat species, with a further increase in temperature limiting its distribution. Similar to continentality (Fig. 4-d) , an inverse relation seems to exist with temperature seasonality. CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted February 22, 2022. ; https://doi.org/10.1101/2022.02.21.22271216 doi: medRxiv preprint was inferred through the probability of presence of P. medius within a district. Categories include 'very high 228 risk (0.75-1)', 'high risk (0.5-0.75)', 'moderate risk (0.25-0.5)', and 'low risk (0-0.25)'. According to the 229 predictions, an expansion and Northward shift of range can be observed as we proceed to the end of the century. . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted February 22, 2022. ; https://doi.org/10.1101/2022.02.21.22271216 doi: medRxiv preprint Risk of spillover events was inferred through the probability of presence of P. medius within a district. Categories include 'very high risk (0.75-1)', 'high risk (0.5-0.75)', 'moderate risk (0.25-0.5)', and 'low risk (0- The current model (Fig. 1) shows an extensive range for P. medius across the East and West coast of India, and Our findings generally predict an expansion in the range of P. medius and a shift towards the North (Fig. 2 & 266 3). The expansion or shift in the range of P. medius could cause NiV spillover in these new areas. Over time, 267 species distribution is predicted to decrease in the high emission scenarios (Fig. 3) . This highlights the adverse 268 effects of anthropogenic and climate change on the host species distribution. The response curves for the future projections show an increase in the suitability of the area for P. medius with 275 increasing urbanisation (Fig. 4) . This implies that the species benefits from urban landscapes as they are 276 provided with alternate resources. This will increase the chances of spillover events as human-bat contact 277 increases [23] . 278 An increase in pastureland (Fig. 4-b) likely results in cutting down of trees that serve as roosting sites. Habitat 279 degradation will lead to further spillover events as human-bat contact increases [23] . 280 The inverse relationship of temperature seasonality (Fig. 4-c) may be an indication of the species' preference 281 for stable temperatures. The suitability for annual mean temperature (Fig. 4-d) With sustainable development, moderate population growth, and global warming of not more than 3 o C by the 287 end of the century, the models predict an expansion of P. medius range (Fig. 2) . As the climate warms slowly 288 and sustainable practices decrease human modification of habitat, the species adapts and expands its range (Fig. 3) . This expansion coupled with 296 stressing factors such as habitat degradation and increased human population could increase the chances of 297 . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted February 22, 2022. ; https://doi.org/10.1101/2022.02.21.22271216 doi: medRxiv preprint spillover in these regions as human contact with the bat species increases. This warrants the application of 298 control measures in these areas to prevent spillovers and to limit human-to-human transmission of NiV. As we 299 move towards 2100 under this scenario a reduction in the suitable areas can be noticed as the high temperatures 300 become unsuitable for the bats. The northward shift is still prominent as the relatively colder climate warms up 301 and becomes suitable to P. medius populations. The decrease in the range towards the South and North-East 302 might be of conservation concern and the bats may undergo a population decline. The few areas where their 303 population is still dense may witness spillover events as viral shedding may increase due to unsuitable 304 temperatures and human activities [67]. The regions at risk of NiV spillover should be targeted to prevent and control outbreaks. Public education 306 regarding NiV, and its transmission routes should be of prime concern as human behaviour seems to be a major 307 driving factor of the spillovers [19] . Increasing surveillance in high-risk areas through combined efforts of the 308 public health, veterinary and wildlife sectors will help in the early detection of outbreaks to implement adequate 309 control measures. The accuracy of our predictions depends on the accuracy of the data used. As spillovers are dynamic events 312 with several contributing factors, several unknown factors may influence spillover events that have not been 313 accounted for in our study. Data for some known factors such as date palm consumption records are 314 unavailable. A future study including such records can be conducted to provide better predictions of spillovers. The effects of a pandemic can be devastating as observed with the current the COVID-19 outbreak. NiV, a 317 fatal disease passed on by bats has the potential to cause such a pandemic by mutating to a form that is easily 318 transmitted from bats to humans and within the human community. Our study predicts an increase in the risk 319 of NiV spillovers throughout India and Bangladesh in the future under all socioeconomic scenarios. To 320 . 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