Effects of natural and socioeconomic factors on dengue transmission in two cities of China from 2006 to 2017

Solid waste management and Aedes aegypti infestation interconnections: A regression tree application

Public health is at the core of all environmental and anthropic impacts. Urban and territorial planners should include public health concerns in their plans. Basic sanitation infrastructure is essential to maintaining public health and social and economic development. This infrastructure deficiency causes diseases, death and economic losses in developing countries. Framing interconnections among health, sanitation, urbanization and circular economy will assist sustainable development goal achievements. This study aims to identify the relationships between solid waste management indicators in Brazil and the Aedes aegypti mosquito infestation index. Regression trees were employed for modelling due to the complexity and characteristics of the data. The analyses were performed separately from data collected from 3501 municipalities and 42 indicators from the country's five regions. Results show that expenses and personnel indicators were the most critical indicators (in the mid-western, southeastern and southern regions), operational (northeastern (NE) region) and management (northern region). The mean absolute errors ranged from 0.803 (southern region) to 2.507 (NE region). Regional analyses indicate that the municipalities with better SWM results display lower infestation rates in buildings and residences. This research is innovative as it analyses infestation rates rather than dengue prevalence, using a machine learning method, in a multidisciplinary research field that needs further study.

Association Between Hydrological Conditions and Dengue Fever Incidence in Coastal Southeastern China From 2013 to 2019

IMPORTANCE

Dengue fever is a climate-sensitive infectious disease. However, its association with local hydrological conditions and the role of city development remain unclear.

OBJECTIVE

To quantify the association between hydrological conditions and dengue fever incidence in China and to explore the modification role of city development in this association.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional study collected data between January 1, 2013, and December 31, 2019, from 54 cities in 4 coastal provinces in southeast China. The Standardized Precipitation Evapotranspiration Index (SPEI) was calculated from ambient temperature and precipitation, with SPEI thresholds of 2 for extreme wet conditions and -2 for extreme dry conditions. The SPEI-dengue fever incidence association was examined over a 6-month lag, and the modification roles of 5 city development dimensions were assessed. Data were analyzed in May 2022.

EXPOSURES

City-level monthly temperature, precipitation, SPEI, and annual city development indicators from 2013 to 2019.

MAIN OUTCOMES AND MEASURES

The primary outcome was city-level monthly dengue fever incidence. Spatiotemporal bayesian hierarchal models were used to examine the SPEI-dengue fever incidence association over a 6-month lag period. An interaction term between SPEI and each city development indicator was added into the model to assess the modification role of city development.

RESULTS

Included in the analysis were 70 006 dengue fever cases reported in 54 cities in 4 provinces in China from 2013 to 2019. Overall, a U-shaped cumulative curve was observed, with wet and dry conditions both associated with increased dengue fever risk. The relative risk [RR] peaked at a 1-month lag for extreme wet conditions (1.27; 95% credible interval [CrI], 1.05-1.53) and at a 6-month lag for extreme dry conditions (1.63; 95% CrI, 1.29-2.05). The RRs of extreme wet and dry conditions were greater in areas with limited economic development, health care resources, and income per capita. Extreme dry conditions were higher and prolonged in areas with more green space per capita (RR, 1.84; 95% CrI, 1.37-2.46). Highly urbanized areas had a higher risk of dengue fever after extreme wet conditions (RR, 1.80; 95% CrI, 1.26-2.56), while less urbanized areas had the highest risk of dengue fever in extreme dry conditions (RR, 1.70; 95% CrI, 1.11-2.60).

CONCLUSIONS AND RELEVANCE

Results of this study showed that extreme hydrological conditions were associated with increased dengue fever incidence within a 6-month lag period, with different dimensions of city development playing various modification roles in this association. These findings may help in developing climate change adaptation strategies and public health interventions against dengue fever.

Climate Change and Vector-Borne Diseases in China: A Review of Evidence and Implications for Risk Management

Simple Summary

Vector-borne diseases are among the most rapidly spreading infectious diseases and are widespread all around the world. In China, many types of vector-borne diseases have been prevalent in different regions, which is a serious public health problem with significant association with meteorological factors and weather events. Under the background of current severe climate change, the outbreaks and transmission of vector-borne diseases have been proven to be impacted greatly due to rapidly changing weather conditions. This study summarizes research progress on the association between climate conditions and all types of vector-borne diseases in China. A total of seven insect-borne diseases, two rodent-borne diseases, and a snail-borne disease were included, among which dengue fever is the most concerning mosquito-borne disease. Temperature, rainfall, and humidity have the most significant effect on vector-borne disease transmission, while the association between weather conditions and vector-borne diseases shows vast differences in China. We also make suggestions about future research based on a review of current studies.

Abstract

Vector-borne diseases have posed a heavy threat to public health, especially in the context of climate change. Currently, there is no comprehensive review of the impact of meteorological factors on all types of vector-borne diseases in China. Through a systematic review of literature between 2000 and 2021, this study summarizes the relationship between climate factors and vector-borne diseases and potential mechanisms of climate change affecting vector-borne diseases. It further examines the regional differences of climate impact. A total of 131 studies in both Chinese and English on 10 vector-borne diseases were included. The number of publications on mosquito-borne diseases is the largest and is increasing, while the number of studies on rodent-borne diseases has been decreasing in the past two decades. Temperature, precipitation, and humidity are the main parameters contributing to the transmission of vector-borne diseases. Both the association and mechanism show vast differences between northern and southern China resulting from nature and social factors. We recommend that more future research should focus on the effect of meteorological factors on mosquito-borne diseases in the era of climate change. Such information will be crucial in facilitating a multi-sectorial response to climate-sensitive diseases in China.

Integrating Spatial Modelling and Space-Time Pattern Mining Analytics for Vector Disease-Related Health Perspectives: A Case of Dengue Fever in Pakistan

The spatial–temporal assessment of vector diseases is imperative to design effective action plans and establish preventive strategies. Therefore, such assessments have potential public health planning-related implications. In this context, we here propose an integrated spatial disease evaluation (I-SpaDE) framework. The I-SpaDE integrates various techniques such as the Kernel Density Estimation, the Optimized Hot Spot Analysis, space–time assessment and prediction, and the Geographically Weighted Regression (GWR). It makes it possible to systematically assess the disease concentrations, patterns/trends, clustering, prediction dynamics, and spatially varying relationships between disease and different associated factors. To demonstrate the applicability and effectiveness of the I-SpaDE, we apply it in the second largest city of Pakistan, namely Lahore, using Dengue Fever (DF) during 2007–2016 as an example vector disease. The most significant clustering is evident during the years 2007–2008, 2010–2011, 2013, and 2016. Mostly, the clusters are found within the city’s central functional area. The prediction analysis shows an inclination of DF distribution from less to more urbanized areas. The results from the GWR show that among various socio-ecological factors, the temperature is the most significantly associated with the DF followed by vegetation and built-up area. While the results are important to understand the DF situation in the study area and have useful implications for public health planning, the proposed framework is flexible, replicable, and robust to be utilized in other similar regions, particularly in developing countries in the tropics and sub-tropics.

Green Space and Health in Mainland China: A Systematic Review

Non-communicable diseases (NCDs) have become a major cause of premature mortality and disabilities in China due to factors concomitant with rapid economic growth and urbanisation over three decades. Promoting green space might be a valuable strategy to help improve population health in China, as well as a range of co-benefits (e.g., increasing resilience to climate change). No systematic review has so far determined the degree of association between green space and health outcomes in China. This review was conducted to address this gap. Five electronic databases were searched using search terms on green space, health, and China. The review of 83 publications that met eligibility criteria reports associations indicative of various health benefits from more green space, including mental health, general health, healthier weight status and anthropometry, and more favorable cardiometabolic and cerebrovascular outcomes. There was insufficient evidence to draw firm conclusions on mortality, birth outcomes, and cognitive function, and findings on respiratory and infectious outcomes were inconsistent and limited. Future work needs to examine the health benefits of particular types and qualities of green spaces, as well as to take advantage of (quasi-)experimental designs to test greening interventions within the context of China's rapid urbanization and economic growth.

Spatial connectivity in mosquito-borne disease models: a systematic review of methods and assumptions

Spatial connectivity plays an important role in mosquito-borne disease transmission. Connectivity can arise for many reasons, including shared environments, vector ecology and human movement. This systematic review synthesizes the spatial methods used to model mosquito-borne diseases, their spatial connectivity assumptions and the data used to inform spatial model components. We identified 248 papers eligible for inclusion. Most used statistical models (84.2%), although mechanistic are increasingly used. We identified 17 spatial models which used one of four methods (spatial covariates, local regression, random effects/fields and movement matrices). Over 80% of studies assumed that connectivity was distance-based despite this approach ignoring distant connections and potentially oversimplifying the process of transmission. Studies were more likely to assume connectivity was driven by human movement if the disease was transmitted by an Aedes mosquito. Connectivity arising from human movement was more commonly assumed in studies using a mechanistic model, likely influenced by a lack of statistical models able to account for these connections. Although models have been increasing in complexity, it is important to select the most appropriate, parsimonious model available based on the research question, disease transmission process, the spatial scale and availability of data, and the way spatial connectivity is assumed to occur.