Beijing Normal University

Although dengue outbreaks cannot be prevented, it is possible to anticipate them. Scientists have recently identified a global climate indicator that may help improve predictions about the magnitude of dengue outbreaks several months in advance. This indicator, which can be used for any world region, is based on temperature fluctuations at the surface of the Indian Ocean. Obtaining reliable long-term predictions could facilitate efforts to tackle this infection, which has been on the rise for several decades and threatens half of the world's population. Although dengue outbreaks cannot be prevented, it is possible to anticipate them. An international research team including scientists from the Institut Pasteur and Beijing Normal University in China has recently identified a global climate indicator that may help improve predictions about the magnitude of dengue outbreaks several months in advance. This indicator, which can be used for any world region, is based on temperature fluctuations at the surface of the Indian Ocean. Obtaining reliable long-term predictions could facilitate efforts to tackle this infection, which has been on the rise for several decades and threatens half of the world's population. The research results were published in the journal Science on May 10, 2024. The ability to anticipate dengue outbreaks is crucial in planning control measures against the mosquitoes that transmit the disease and mobilizing hospital staff and equipment. And this is vitally important, because although vaccines have been developed, there is no specific treatment for the symptoms of this "tropical influenza," and the severity of outbreaks can vary hugely from one year to the next. "The dynamics of dengue are complex because the virus responsible for infection exists in four different forms, or serotypes, which can change from one year to the next and one country to the next," explains Simon Cauchemez, joint last author of the study and Head of the Mathematical Modeling of Infectious Diseases Unit at the Institut Pasteur. "So the magnitude of dengue outbreaks can vary considerably from one season to the next." We now know that the reproduction and infectivity of Aedes genus mosquitoes that transmit dengue viruses, and by extension the transmission rate and scale of outbreaks, are closely correlated with local temperature and rainfall. But these parameters can only be predicted between two weeks and three months in advance, and the quality of forecasts decreases rapidly for longer-term predictions. Global climate indicators like El Niño-Southern Oscillation (ENSO) can generally be predicted over a longer period, beyond six months. An international team therefore decided to study 30 global climate indicators to determine whether monitoring such indicators could help predict dengue outbreaks further in advance. The team compiled two large datasets: the total number of annual dengue cases reported in 46 countries in South-East Asia and America over 30 years (1990-2019), and also the monthly number of dengue cases in 24 countries over six years (2014-2019). They found that of all the indicators under consideration, the Indian Ocean basin-wide (IOBW) index, which measures temperature fluctuations at the surface of the Indian Ocean, was the global indicator that was most closely correlated to annual dengue incidence in both the northern and southern hemispheres. "Our results revealed that incorporating the IOBW index into our mathematical model resulted in predictions that closely matched real-world data, compared to the model excluding the IOBW index," notes Huaiyu Tian, co-last author of the study and Director of the Center for Global Change and Public Health, Beijing Normal University. "The extended lead time and improved predictive ability underscore the significance of the IOBW index in dengue forecasting and early warning systems." These interesting theoretical findings will need to be validated in real conditions. "Our aim is to develop predictive models for dengue outbreaks in Guadeloupe, French Guiana and Martinique, and we will now explore whether the IOBW index can effectively improve these predictions," explains Simon Cauchemez. "Climate is not the only factor that influences dengue outbreaks. For these predictive models we will also need to take into account other factors like immunity levels in the population, strains previously in circulation, etc." If the findings are borne out, the new indicator could help improve the prediction of dengue outbreaks, thereby also improving efforts to tackle this infectious disease, which affects 50,000 million people each year. The incidence of dengue has risen dramatically in recent years, especially in mainland France. Between January 1 and April 19, 2024, 1,679 imported dengue cases were reported to Santé publique France, compared with 131 over the same period in 2023.

With climate change and rising urbanization, the likelihood and severity of urban flooding are increasing. But not all city blocks are created equal. Researchers investigated how urban layout and building structures contribute to pedestrian safety during flooding. Based on their simulated results, the team recommends modifying building corners and protective block layouts to reduce pedestrian risk. A city's skyline -- the distinctive shapes and arrangements of its buildings -- impacts the safety of its population during floods. When the streets flood, pedestrians can be swept under the current and injured or killed. With climate change and rising urbanization, the likelihood and severity of urban flooding are increasing. Not all city blocks are created equal. In Physics of Fluids, an AIP Publishing journal, researchers from Beijing Normal University, Beijing Hydrological Center, and the China Institute of Water Resources and Hydropower Research investigated how city design contributes to pedestrian safety during flooding. "Climate change leads to an increasing trend of extreme precipitation events in terms of frequency and intensity," said author Zhong-Fan Zhu. "Rapid urbanization alters the hydrological properties of the underlying surface in urban areas. For example, previous forestland, wetland, and agricultural land have been paved to construct impervious, urban lands. These factors contribute to frequency occurrences of urban flood events." The researchers experimentally identified the flood conditions that make pedestrians vulnerable and utilized computer simulations of different city block patterns, building heights, and street widths to assess the configurations that best protect people. Each city has unique buildings and building configurations. The team simulated three different urban block layouts: buildings neatly arranged and equally spaced in columns and rows, buildings offset and staggered, and a square tightly outlined by buildings with just four buildings enclosed within. When buildings are arranged in a line, as in the grid and enclosed layout, they provide a zone of safety by blocking some of the water and wind. The staggered approach has none of this protection and more danger zones due to increased water and wind circulation. Altering the building shape can also protect pedestrians. Rounding or adding recesses to building corners significantly reduced areas of dangerously high floodwater and windspeed. However, this intervention also somewhat decreased the safety zone. Wind was a critical, yet complex, factor in determining safety. "In some cases, the floodwater does not cause pedestrian instability, but adding the wind force will lead to a dangerous situation," said Zhu. "However, in other cases, the wind will help to maintain pedestrian stability and protect against floodwater. It seems like that wind is like a 'double-edged sword.'" Different building height arrangements can help mitigate the negative impacts of wind. Cities looking to expand should consider enclosed block arrangements, buildings with rounded or even circular footprints, and potentially consult with a physicist.

A new study now provides a global examination of drought-pluvial volatility -- or the tendency to shift from one weather extreme to another. Over the last two decades an estimated three billion people have been affected by water-related natural disasters such as droughts and floods. Climate change is expected to increase the frequency of these hydro hazards, with some prognosticators estimating there will be upwards of $3.7 trillion in water-related damage over the next 30 years in the U.S. alone. Beyond damaging homes and infrastructure, severe wet and dry spells will also devastate crops and deplete water reservoirs. An increasing area of interest to researchers is the frequency of compound drought and pluvial flooding (caused by quick, heavy rainfall or sustained rainfall beyond the norm), which is when both occur in succession in the same area within a year of each other. Historically, this level of coincidence has been under-examined. Of similar interest is when the reverse happens: extreme rainfall followed by a meteorological drought. Meteorological drought is when dry weather patterns prevail, which can eventually trigger hydrological drought, leading to dry streams and plunging reservoir levels, such as what happened at Lake Mead in 2022. A new study co-authored by researchers in the University of Arkansas Department of Geosciences, as well as colleagues in China, now provides a global examination of drought-pluvial volatility -- or the tendency to shift from one extreme to another (from dry to wet or wet to dry) in a short period of time. Yichan Li, a Ph.D. candidate at the U of A, was the first of four authors on the paper, "Observational Uncertainty for Global Drought-Pluvial Volatility," published in Water Resources Research, while Linyin Cheng, an assistant professor of geosciences, was second author. The study looks at extreme dry-to-wet and wet-to-dry transitions over the past seven decades through event coincidence analysis, a method of quantifying the number of consecutive extreme events that also considers instantaneous or lagged responses within an uncertain period between them. The study used three widely used climate data sets to provide evidence of increased drought-pluvial volatility on time scales of less than a year. The team also evaluated the accuracy of these data sets, finding varying strengths and weaknesses of each due to observational uncertainties in data collection. For instance, the remoteness of a region may play a role in collecting accurate data. Averaged out at the global scale, the team found that 15.46% of all meteorological droughts were succeeded by a pluvial the following season. The wet-to-dry transition percentage proved remarkably similar: 15.49%. However, prominent differences exist when looking at particular regions. Toward that end, the study provides a map demonstrating how incidents of these two phenomena are distributed globally. Overall, the spatial pattern of extreme dry-to-wet and wet-to-dry events' coincidence rates is largely in agreement among the three data sets, though there is prominent regional variability. For instance, in Eurasia since the mid-20th century, there is a relatively low probability for meteorological droughts transitioning to pluvials, but a higher chance for the opposite scenario, rapid shifts from wet to dry events. A similar pattern also exists over western North America, which sees severe wet to dry transitions at a frequency greater than 17% on average. Conversely, South Asia and Australia are more prone to immediate transitions from meteorological droughts to pluvials. The authors noted: "Our findings indicate that differences associated with drought-pluvial volatility among the considered observations are in many regions larger than that of their single events [droughts or pluvials alone], highlighting a need of to use multiple independent observation-based data sets for more robust examinations when studying such compound extreme events." Ultimately, the authors stress the need to use multiple independent observation-based data sets when analyzing extreme, compound dry-to-wet events. This will provide clearer guidelines for climate-related decision making, especially water resources planning, as well as ensure better accuracy when modeling future weather events. Additional co-authors in the paper included Chiyun Miao, with Beijing Normal University and Zhiyong Liu, with Sun Yat-sen University.