Spatio-temporal and neighborhood characteristics of two dengue outbreaks in two arid cities of Mexico

Aedes aegypti abundance in urban neighborhoods of Maricopa County, Arizona, is linked to increasing socioeconomic status and tree cover

BACKGROUND

Understanding coupled human-environment factors which promote Aedes aegypti abundance is critical to preventing the spread of Zika, chikungunya, yellow fever and dengue viruses. High temperatures and aridity theoretically make arid lands inhospitable for Ae. aegypti mosquitoes, yet their populations are well established in many desert cities.

METHODS

We investigated associations between socioeconomic and built environment factors and Ae. aegypti abundance in Maricopa County, Arizona, home to Phoenix metropolitan area. Maricopa County Environmental Services conducts weekly mosquito surveillance with CO2-baited Encephalitis Vector Survey or BG-Sentinel traps at > 850 locations throughout the county. Counts of adult female Ae. aegypti from 2014 to 2017 were joined with US Census data, precipitation and temperature data, and 2015 land cover from high-resolution (1 m) aerial images from the National Agricultural Imagery Program.

RESULTS

From 139,729 trap-nights, 107,116 Ae. aegypti females were captured. Counts were significantly positively associated with higher socioeconomic status. This association was partially explained by higher densities of non-native landscaping in wealthier neighborhoods; a 1% increase in the density of tree cover around the trap was associated with a ~ 7% higher count of Ae. aegypti (95% CI: 6-9%).

CONCLUSIONS

Many models predict that climate change will drive aridification in some heavily populated regions, including those where Ae. aegypti are widespread. City climate change adaptation plans often include green spaces and vegetation cover to increase resilience to extreme heat, but these may unintentionally create hospitable microclimates for Ae. aegypti. This possible outcome should be addressed to reduce the potential for outbreaks of Aedes-borne diseases in desert cities.

Differences in Longevity and Temperature-Driven Extrinsic Incubation Period Correlate with Varying Dengue Risk in the Arizona-Sonora Desert Region

Dengue transmission is determined by a complex set of interactions between the environment, Aedes aegypti mosquitoes, dengue viruses, and humans. Emergence in new geographic areas can be unpredictable, with some regions having established mosquito populations for decades without locally acquired transmission. Key factors such as mosquito longevity, temperature-driven extrinsic incubation period (EIP), and vector-human contact can strongly influence the potential for disease transmission. To assess how these factors interact at the edge of the geographical range of dengue virus transmission, we conducted mosquito sampling in multiple urban areas located throughout the Arizona-Sonora desert region during the summer rainy seasons from 2013 to 2015. Mosquito population age structure, reflecting mosquito survivorship, was measured using a combination of parity analysis and relative gene expression of an age-related gene, SCP-1. Bloodmeal analysis was conducted on field collected blood-fed mosquitoes. Site-specific temperature was used to estimate the EIP, and this predicted EIP combined with mosquito age were combined to estimate the abundance of "potential" vectors (i.e., mosquitoes old enough to survive the EIP). Comparisons were made across cities by month and year. The dengue endemic cities Hermosillo and Ciudad Obregon, both in the state of Sonora, Mexico, had higher abundance of potential vectors than non-endemic Nogales, Sonora, Mexico. Interestingly, Tucson, Arizona consistently had a higher estimated abundance of potential vectors than dengue endemic regions of Sonora, Mexico. There were no observed city-level differences in species composition of blood meals. Combined, these data offer insights into the critical factors required for dengue transmission at the ecological edge of the mosquito's range. However, further research is needed to integrate an understanding of how social and additional environmental factors constrain and enhance dengue transmission in emerging regions.

Relationship between Urban Environmental Components and Dengue Prevalence in Dhaka City-An Approach of Spatial Analysis of Satellite Remote Sensing, Hydro-Climatic, and Census Dengue Data

Dengue fever is a tropical viral disease mostly spread by the Aedes aegypti mosquito across the globe. Each year, millions of people have dengue fever, and many die as a result. Since 2002, the severity of dengue in Bangladesh has increased, and in 2019, it reached its worst level ever. This research used satellite imagery to determine the spatial relationship between urban environmental components (UEC) and dengue incidence in Dhaka in 2019. Land surface temperature (LST), urban heat-island (UHI), land-use-land-cover (LULC), population census, and dengue patient data were evaluated. On the other hand, the temporal association between dengue and 2019 UEC data for Dhaka city, such as precipitation, relative humidity, and temperature, were explored. The calculation indicates that the LST in the research region varies between 21.59 and 33.33 degrees Celsius. Multiple UHIs are present within the city, with LST values ranging from 27 to 32 degrees Celsius. In 2019, these UHIs had a higher incidence of dengue. NDVI values between 0.18 and 1 indicate the presence of vegetation and plants, and the NDWI identifies waterbodies with values between 0 and 1. About 2.51%, 2.66%, 12.81%, and 82% of the city is comprised of water, bare ground, vegetation, and settlement, respectively. The kernel density estimate of dengue data reveals that the majority of dengue cases were concentrated in the city's north edge, south, north-west, and center. The dengue risk map was created by combining all of these spatial outputs (LST, UHI, LULC, population density, and dengue data) and revealed that UHIs of Dhaka are places with high ground temperature and lesser vegetation, waterbodies, and dense urban characteristics, with the highest incidence of dengue. The average yearly temperature in 2019 was 25.26 degrees Celsius. May was the warmest month, with an average monthly temperature of 28.83 degrees Celsius. The monsoon and post-monsoon seasons (middle of March to middle of September) of 2019 sustained higher ambient temperatures (>26 °C), greater relative humidity (>80%), and at least 150 mm of precipitation. The study reveals that dengue transmits faster under climatological circumstances characterized by higher temperatures, relative humidity, and precipitation.

Household and climate factors influence Aedes aegypti presence in the arid city of Huaquillas, Ecuador

Arboviruses transmitted by Aedes aegypti (e.g., dengue, chikungunya, Zika) are of major public health concern on the arid coastal border of Ecuador and Peru. This high transit border is a critical disease surveillance site due to human movement-associated risk of transmission. Local level studies are thus integral to capturing the dynamics and distribution of vector populations and social-ecological drivers of risk, to inform targeted public health interventions. Our study examines factors associated with household-level Ae. aegypti presence in Huaquillas, Ecuador, while accounting for spatial and temporal effects. From January to May of 2017, adult mosquitoes were collected from a cohort of households (n = 63) in clusters (n = 10), across the city of Huaquillas, using aspirator backpacks. Household surveys describing housing conditions, demographics, economics, travel, disease prevention, and city services were conducted by local enumerators. This study was conducted during the normal arbovirus transmission season (January—May), but during an exceptionally dry year. Household level Ae. aegypti presence peaked in February, and counts were highest in weeks with high temperatures and a week after increased rainfall. Univariate analyses with proportional odds logistic regression were used to explore household social-ecological variables and female Ae. aegypti presence. We found that homes were more likely to have Ae. aegypti when households had interruptions in piped water service. Ae. aegypti presence was less likely in households with septic systems. Based on our findings, infrastructure access and seasonal climate are important considerations for vector control in this city, and even in dry years, the arid environment of Huaquillas supports Ae. aegypti breeding habitat.

Mosquito transmitted infectious diseases are a growing concern around the world. The yellow fever mosquito (Aedes aegypti) has been responsible for recent major outbreaks of disease, including dengue fever and Zika. This mosquito prefers to bite humans and lay its eggs in artificial containers such as water tanks and planters. This makes Ae. aegypti well suited to become established in growing urban areas. Controlling these mosquitoes has been an important way to reduce the risk of disease transmission. Studies that are undertaken to understand local factors that contribute to the continued survival of the mosquito can be used to inform control practices. We conducted a study in the largest Ecuadorian city on the border of Peru where we collected adult mosquitoes from houses and surveyed household members about their behaviors, perceptions, and housing infrastructure associated with the mosquito vector. Mosquitoes were most numerous in weeks with high temperatures and a week after increased rainfall. We found that houses that had unreliable water service were more likely have mosquitoes present, while houses that used septic systems were less likely to have mosquitoes present.

Dengue models based on machine learning techniques: A systematic literature review

BACKGROUND

Dengue modeling is a research topic that has increased in recent years. Early prediction and decision-making are key factors to control dengue. This Systematic Literature Review (SLR) analyzes three modeling approaches of dengue: diagnostic, epidemic, intervention. These approaches require models of prediction, prescription and optimization. This SLR establishes the state-of-the-art in dengue modeling, using machine learning, in the last years.

METHODS

Several databases were selected to search the articles. The selection was made based on Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology. Sixty-four articles were obtained and analyzed to describe their strengths and limitations. Finally, challenges and opportunities for research on machine-learning for dengue modeling were identified.

RESULTS

Logistic regression was the most used modeling approach for the diagnosis of dengue (59.1%). The analysis of the epidemic approach showed that linear regression (17.4%) is the most used technique within the spatial analysis. Finally, the most used intervention modeling is General Linear Model with 70%.

CONCLUSIONS

We conclude that cause-effect models may improve diagnosis and understanding of dengue. Models that manage uncertainty can also be helpful, because of low data-quality in healthcare. Finally, decentralization of data, using federated learning, may decrease computational costs and allow model building without compromising data security.

Evaluation of Neighborhood Socio-Economic Status, as Measured by the Delphi Method, on Dengue Fever Distribution in Jeddah City, Saudi Arabia

Dengue fever, a mosquito-transmitted viral disease, is present in many neighborhoods in Jeddah City, Saudi Arabia. One factor likely to affect its distribution is the socio-economic status of local neighborhoods; however, the absence of socio-economic census data in Saudi Arabia has precluded detailed investigation. This study aims to develop a proxy measure of socio-economic status in Jeddah City in order to assess its relationship with the occurrence of dengue fever. The Delphi method was used to assess the socio-economic status (high, medium or low) of local neighborhoods in Jeddah City. A Geographic Information System (GIS) was applied to understand the distribution of dengue fever according to the socio-economic status of Jeddah City neighborhoods. Low-socio-economic status neighborhoods in south Jeddah City, with poor environmental conditions and high levels of poverty and population density, reported most cases of dengue fever. Nevertheless, dengue continues to increase in high socio-economic status neighborhoods in the northern part of the city, possibly due to ideal breeding conditions caused by the presence of standing water associated with high levels of construction. Moreover, the low-socioeconomic-status neighborhoods had the highest average number of cases, being 3.95 times that of high-status neighborhoods for the period 2006–2009. The Delphi approach can produce a useful and robust measure of socio-economic status for use in the analysis of patterns of dengue fever. Results suggest that there are nuances in the relationship between socio-economic status and dengue that indicate that higher status areas are also at risk. A useful additional tool for researchers in Saudi Arabia would be the development of census data or other systematic measures that allow socio-economic status to be included in spatial analyses of dengue fever and other diseases.

Análise espacial da distribuição dos casos de dengue e sua relação com fatores socioambientais no estado da Paraíba, Brasil, 2007-2016

RESUMO A dengue é um grave problema de saúde pública, principalmente em países que apresentam condições socioambientais propícias para o desenvolvimento e proliferação do seu agente transmissor. Este estudo teve como objetivo analisar a distribuição espacial da incidência da dengue no estado da Paraíba entre 2007 e 2016, avaliando a existência de dependência geográfica e sua relação com fatores socioeconômicos e ambientais. Estudo ecológico, tendo com unidade de análise os 223 municípios do estado. Utilizaram-se o Índice de Moran global e local e a estatística c de Geary para avaliar a autocorrelação espacial da dengue e a associação com variáveis socioambientais. As análises foram realizadas por meio do software estatístico R Core Team versão 3.3.2. Ao analisar a distribuição de casos de dengue nos municípios da Paraíba, pode-se identificar que a doença vem avançando e acometendo maior número de cidades a cada ano. A doença esteve presente em todos as cidades analisadas, o que demonstrou a necessidade de implementar ações de prevenção da doença em todo o estado. Mediante esta pesquisa, ficou claro que a dengue, no estado da Paraíba, não é determinada por fator único e isolado, mas sim, pela combinação de vários fatores do contexto socioeconômico e ambiental.

Preparedness Through Urban Resilience

This book explores the topic of resilience at the city level. The focus is more on outbreak events at the city level, or how cities should prepare and react in facing the larger events of epidemic and pandemic.

Spatiotemporal Heterogeneity in the Distribution of Chikungunya and Zika Virus Case Incidences during their 2014 to 2016 Epidemics in Barranquilla, Colombia

Chikungunya virus (CHIKV) and Zika virus (ZIKV) have recently emerged as globally important infections. This study aimed to explore the spatiotemporal heterogeneity in the occurrence of CHIKV and ZIKV outbreaks throughout the major international seaport city of Barranquilla, Colombia in 2014 and 2016 and the potential for clustering. Incidence data were fitted using multiple Bayesian Poisson models based on multiple explanatory variables as potential risk factors identified from other studies and options for random effects. A best fit model was used to analyse their case incidence risks and identify any risk factors during their epidemics. Neighbourhoods in the northern region were hotspots for both CHIKV and ZIKV outbreaks. Additional hotspots occurred in the southwestern and some eastern/southeastern areas during their outbreaks containing part of, or immediately adjacent to, the major circular city road with its import/export cargo warehouses and harbour area. Multivariate conditional autoregressive models strongly identified higher socioeconomic strata and living in a neighbourhood near a major road as risk factors for ZIKV case incidences. These findings will help to appropriately focus vector control efforts but also challenge the belief that these infections are driven by social vulnerability and merit further study both in Barranquilla and throughout the world's tropical and subtropical regions.

VECTOS: An Integrated System for Monitoring Risk Factors Associated With Urban Arbovirus Transmission

To strengthen local surveillance of mosquito-borne viral diseases such as dengue and Zika, a multidisciplinary team developed an integrated web-based information system called VECTOS that captures geo-referenced entomological, epidemiological, and social data. The system has revealed previously unidentified features, such as specific neighborhoods, at persistently high risk.

In Colombia, as in many Latin American countries, decision making and development of effective strategies for vector control of urban diseases such as dengue, Zika, and chikungunya is challenging for local health authorities. The heterogeneity of transmission in urban areas requires an efficient risk-based allocation of resources to control measures. With the objective of strengthening the capacity of local surveillance systems to identify variables that favor urban arboviral transmission, a multidisciplinary research team collaborated with the local Secretary of Health officials of 3 municipalities in Colombia (Giron, Yopal, and Buga), in the design of an integrated information system called VECTOS from 2015 to 2018. Information and communication technologies were used to develop 2 mobile applications to capture entomological and social information, as well as a web-based system for the collection, geo-referencing, and integrated information analysis using free geospatial software. This system facilitates the capture and analysis of epidemiological information from the Colombian national surveillance system (SIVIGILA), periodic entomological surveys—mosquito larvae and pupae in premises and peridomestic breeding sites—and surveys of knowledge, attitudes, and practices (KAP) in a spatial and temporal context at the neighborhood level. The data collected in VECTOS are mapped and visualized in graphical reports. The system enables real-time monitoring of weekly epidemiological indicators, entomological indices, and social surveys. Additionally, the system enables risk stratification of neighborhoods, using selected epidemiological, entomological, demographic, and environmental variables. This article describes the VECTOS system and the lessons learned during its development and use. The joint analysis of epidemiological and entomological data within a geographic information system in VECTOS gives better insight to the routinely collected data and identifies the heterogeneity of risk factors between neighborhoods. We expect the system to continue to strengthen vector control programs in evidence-based decision making and in the design and enhanced follow-up of vector control strategies.

Spatial analysis of probable cases of dengue fever, chikungunya fever and zika virus infections in Maranhao State, Brazil

Dengue fever, chikungunya fever, and zika virus infections are increasing public health problems in the world, the last two diseases having recently emerged in Brazil. This ecological study employed spatial analysis of probable cases of dengue fever, chikungunya fever, and zika virus infections reported to the National Mandatory Reporting System (SINAN) in Maranhao State from 2015 to 2016. The software GeoDa version 1.10 was used for calculating global and local Moran indices. The global Moran index identified a significant autocorrelation of incidence rates of dengue (I=0.10; p=0.009) and zika (I=0.07; p=0.03). The study found a positive spatial correlation between dengue and the population density (I=0.31; p<0.001) and a negative correlation with the Performance Index of Unified Health System (PIUHS) by basic care coverage (I=-0.08; p=0.01). Regarding chikungunya fever, there were positive spatial correlations with the population density (I=0.06; p=0.03) and the Municipal Human Development Index (MHDI) (I=0.10; p=0.002), and a negative correlation with the Gini index (I=-0.01; p<0.001) and the PIUHS by basic care coverage (I=-0.18; p<0.001). Lastly, we found positive spatial correlations between Zika virus infections and the population density (I=0.13; p=0.005) and the MHDI (I=0.12; p<0.001), as well as a negative correlation with the Gini index (I=-0.11; p<0.001) and the PIUHS by basic care coverage (I=-0.05; p=0.03). Our results suggest that several socio-demographic factors influenced the occurrence of dengue fever, chikungunya fever, and zika virus infections in Maranhao State.