Dengue is a systemic viral infection transmitted between humans by Aedes mosquitoes. For some patients, dengue is a life-threatening illness. There are currently no licensed vaccines or specific therapeutics, and substantial vector control efforts have not stopped its rapid emergence and global spread. The contemporary worldwide distribution of the risk of dengue virus infection and its public health burden are poorly known. Here we undertake an exhaustive assembly of known records of dengue occurrence worldwide, and use a formal modelling framework to map the global distribution of dengue risk. We then pair the resulting risk map with detailed longitudinal information from dengue cohort studies and population surfaces to infer the public health burden of dengue in 2010. We predict dengue to be ubiquitous throughout the tropics, with local spatial variations in risk influenced strongly by rainfall, temperature and the degree of urbanization. Using cartographic approaches, we estimate there to be 390 million (95% credible interval 284-528) dengue infections per year, of which 96 million (67-136) manifest apparently (any level of disease severity). This infection total is more than three times the dengue burden estimate of the World Health Organization. Stratification of our estimates by country allows comparison with national dengue reporting, after taking into account the probability of an apparent infection being formally reported. The most notable differences are discussed. These new risk maps and infection estimates provide novel insights into the global, regional and national public health burden imposed by dengue. We anticipate that they will provide a starting point for a wider discussion about the global impact of this disease and will help to guide improvements in disease control strategies using vaccine, drug and vector control methods, and in their economic evaluation.

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The global distribution and burden of dengue

Settlements in coastal lowlands are especially vulnerable to risks resulting from climate change, yet these lowlands are densely settled and growing rapidly. In this paper, we undertake the fi rst global review of the population and urban settlement patterns in the Low Elevation Coastal Zone (LECZ), defi ned here as the contiguous area along the coast that is less than 10 metres above sea level. Overall, this zone covers 2 per cent of the world's land area but contains 10 per cent of the world's population and 13 per cent of the world's urban population. A dis- proportionate number of the countries with a large share of their population in this zone are small island countries, but most of the countries with large populations in the zone are large countries with heavily populated delta regions. On average, the Least Developed Countries have a higher share of their population living in the zone (14 per cent) than do OECD countries (10 per cent), with even greater disparities in the urban shares (21 per cent compared to 11 per cent). Almost two- thirds of urban settlements with populations greater than 5 million fall, at least partly, in the zone. In some countries (most notably China), urbanization is driving a movement in population towards the coast. Reducing the risk of disasters related to climate change in coastal settlements will require a combination of mitigation, migration and settlement modifi cation.

https://journals.sagepub.com/doi/pdf/10.1177/0956247807076960

The rising tide: assessing the risks of climate change and human settlements in low elevation coastal zones:

GDP growth is often measured poorly for countries and rarely measured at all for cities or subnational regions. We propose a readily available proxy: satellite data on lights at night. We develop a statistical framework that uses lights growth to augment existing income growth measures, under the assumption that measurement error in using observed light as an indicator of income is uncorrelated with measurement error in national income accounts. For countries with good national income accounts data, information on growth of lights is of marginal value in estimating the true growth rate of income, while for countries with the worst national income accounts, the optimal estimate of true income growth is a composite with roughly equal weights. Among poor-data countries, our new estimate of average annual growth differs by as much as 3 percentage points from official data. Lights data also allow for measurement of income growth in sub- and supranational regions. As an application, we examine growth in Sub Saharan African regions over the last 17 years. We find that real incomes in non-coastal areas have grown faster by 1/3 of an annual percentage point than coastal areas; non-malarial areas have grown faster than malarial ones by 1/3 to 2/3 annual percent points; and primate city regions have grown no faster than hinterland areas. Such applications point toward a research program in which "empirical growth" need no longer be synonymous with "national income accounts."

https://papers.ssrn.com/sol3/Delivery.cfm/nber_w15199.pdf?abstractid=1442664&mirid=1

Measuring Economic Growth from Outer Space

Dengue and chikungunya are increasing global public health concerns due to their rapid geographical spread and increasing disease burden. Knowledge of the contemporary distribution of their shared vectors, Aedes aegypti and Aedes albopictus remains incomplete and is complicated by an ongoing range expansion fuelled by increased global trade and travel. Mapping the global distribution of these vectors and the geographical determinants of their ranges is essential for public health planning. Here we compile the largest contemporary database for both species and pair it with relevant environmental variables predicting their global distribution. We show Aedes distributions to be the widest ever recorded; now extensive in all continents, including North America and Europe. These maps will help define the spatial limits of current autochthonous transmission of dengue and chikungunya viruses. It is only with this kind of rigorous entomological baseline that we can hope to project future health impacts of these viruses.

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The global distribution of the arbovirus vectors Aedes aegypti and Ae. Albopictus

Background: Dengue is a growing problem both in its geographical spread and in its intensity, and yet current global distribution remains highly uncertain. Challenges in diagnosis and diagnostic methods as well as highly variable national health systems mean no single data source can reliably estimate the distribution of this disease. As such, there is a lack of agreement on national dengue status among international health organisations. Here we bring together all available information on dengue occurrence using a novel approach to produce an evidence consensus map of the disease range that highlights nations with an uncertain dengue status. Methods/Principal Findings: A baseline methodology was used to assess a range of evidence for each country. In regions where dengue status was uncertain, additional evidence types were included to either clarify dengue status or confirm that it is unknown at this time. An algorithm was developed that assesses evidence quality and consistency, giving each country an evidence consensus score. Using this approach, we were able to generate a contemporary global map of national-level dengue status that assigns a relative measure of certainty and identifies gaps in the available evidence. Conclusion: The map produced here provides a list of 128 countries for which there is good evidence of dengue occurrence, including 36 countries that have previously been classified as dengue-free by the World Health Organization and/or the US Centers for Disease Control. It also identifies disease surveillance needs, which we list in full. The disease extents and limits determined here using evidence consensus, marks the beginning of a five-year study to advance the mapping of dengue virus transmission and disease risk. Completion of this first step has allowed us to produce a preliminary estimate of population at risk with an upper bound of 3.97 billion people. This figure will be refined in future work.

/pdf/refining-the-global-spatial-limits-of-dengue-virus-f8emry0wk5.pdf

Refining the global spatial limits of dengue virus transmission by evidence-based consensus

Spatial analysis of global urban extent from DMSP-OLS night lights

Evaluating the total numbers of people at risk from infectious disease in the world requires not just tabular population data, but data that are spatially explicit and global in extent at a moderate resolution. This review describes the basic methods for constructing estimates of global population distribution with attention to recent advances in improving both spatial and temporal resolution. To evaluate the optimal resolution for the study of disease, the native resolution of the data inputs as well as that of the resulting outputs are discussed. Assumptions used to produce different population data sets are also described, with their implications for the study of infectious disease. Lastly, the application of these population data sets in studies to assess disease distribution and health impacts is reviewed. The data described in this review are distributed in the accompanying DVD.

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Determining global population distribution: methods, applications and data.

What is known about the urban world is largely derived from local knowledge. This paper showcases substantial efforts at new data integration with existing technologies to develop a new suite of global datasets on urban population and extents. These new databases far surpass past efforts to construct a systematic global database of urban areas by combining census and satellite data and methods of analysis, in an integrated geospatial framework. The resulting data allow for inquiry into analysis urban issues and population by environmental and other ecological characteristics in novel ways. This paper focuses on the methodologies employed to construct these new datasets. Summary results regarding population distribution at continentand global-levels are also given, , as well as suggestions for future research.

/pdf/the-distribution-of-people-and-the-dimension-of-place-19zo23vur3.pdf

The Distribution of People and the Dimension of Place: Methodologies to Improve the Global Estimation of Urban Extents

In this study we investigate the question of whether urban and suburban areas in the United States can be defined on the basis of demographic and/or physical characteristics, in particular, population density and vegetation abundance. We investigate their relationship in the cities of Atlanta, Chicago, Los Angeles, New York, Phoenix, and Seattle and compare the results with the USGS National Land Cover Dataset’s urban classes. The bimodal distribution of U.S. population density provides a demographic basis for distinguishing rural and suburban land use, while a distinct tail of high population densities (� 10,000 people/km 2 ) corresponds to high intensity urban residential cores. Results show that the maximum vegetation fraction diminishes with increasing population density, but the spectral heterogeneity at pixel scales still results in a wide range of vegetation fractions within demographically urban and suburban areas. None of the USGS residential classes show a strong correspondence to either vegetation fraction or population density. However, quantitative characterization of vegetation abundance provides a basis for comparison of the physical environments of suburban areas. We suggest that classification schemes based on spectral heterogeneity at multiple pixel scales, supplemented by auxiliary data sources, may provide a more accurate and self-consistent way to quantify urban land use and analyze urban growth than traditional thematic classification schemes.

Analysis of Urban Land Cover and Population Density in the United States

Reflectance characteristics of human settlements influence energy fluxes in the physical environment as well as our ability to monitor urban growth with satellite-based sensors. Spectral heterogeneity at the scales of 10 to 30 meters complicate the traditional land cover classifications derived from moderate resolution satellite imagery in urban and suburban areas. In this study we consider population density and vegetation abundance as the principal demographic and physical characteristics in urban and suburban areas of the U.S.A. We investigate their relationship in the cities of Atlanta, Chicago, Los Angeles, New York, Phoenix and Seattle and compare the results with the USGS National Land Cover Dataset’s urban classes. The multimodal population density distribution of the U.S.A. implies that it is possible to characterize suburban areas as those with population densities between 100 and 10,000 people/km, with rural areas at densities below 100 people/km and urban areas at densities above 10,000 people/km. We find that maximum vegetation fraction diminishes with increasing population density over the full range of densities, but the spectral heterogeneity at pixel scales still results in a wide range of vegetation fractions in demographically urban and suburban areas. The resolution difference between census units and the Landsat sensor’s field of view does not allow for a pixel scale spectral characterization of suburban land cover that is consistent with population density. A classification scheme based on spectral heterogeneity at multiple pixel scales, supplemented by auxiliary data sources, may provide a more accurate way to analyze urban growth.

/pdf/vegetation-and-population-density-in-urban-and-suburban-3nnygecub6.pdf

Francesca Pozzi

Papers

Spatial analysis of global urban extent from DMSP-OLS night lights

Determining global population distribution: methods, applications and data.

The Distribution of People and the Dimension of Place: Methodologies to Improve the Global Estimation of Urban Extents

Analysis of Urban Land Cover and Population Density in the United States

Vegetation and population density in urban and suburban areas in the u.s.a