Early Detection for Dengue Using Local Indicator of Spatial Association (LISA) Analysis

Spatial patterns of maternal and neonatal continuum of care use and its correlations with women's empowerment

BACKGROUND

The continuum of care (CoC) in maternal health refers to the continuity of individual reproductive health care across the antenatal, intrapartum, and postnatal periods. The CoC is an indicator of the quality of maternal and newborn health outcomes and women's empowerment is crucial to improving maternal and neonatal health service access and utilisation.

OBJECTIVE

To examine the spatial patterns of continuum of care use for maternal and neonatal health services and its correlation with women's empowerment.

METHODS

We analysed data from the Ethiopian Demographic and Health Surveys (EDHS) of 2011 and 2016. All women aged 15-49 who had live births in the preceding five years of the DHS surveys were included in the analysis. We measured the continuum of care using the modified co-coverage index (CoCI), which consisted of six indicators. Women's empowerment was assessed using a validated survey-based Women's Empowerment (SWPER) index. We used the Getis-Ord-Gi* spatial analysis tool to portray locations with clusters of CoC service use and spatial correlations between CoC use and women empowerment.

RESULTS

None of the newborn-mother pairs in the 2011 survey received the entire continuum of care and only 2.5% of newborn-mother pairs received the full range of continuum of care services in the 2016 survey. In 2016, 6.9% of mother-newborn pairs received the basic CoC services (four or more antenatal care [ANC] visits, skilled birth attendance [SBA], and postnatal care [PNC]), and no mother-newborn pair received all three services at the same time in 2011. The Amhara, Afar, and Somali regional states had the least CoC service use in both surveys. There was a positive spatial correlation between CoC use and women's empowerment domains.

CONCLUSION

Our analysis showed that the use of four or more ANC visits, SBS, newborn PNC, Bacillus Calmette-Guérin (BCG) vaccine uptake, and tetanus toxoid protection at birth were low in Ethiopia. Women empowerment domains were found to have a positive spatial correlation with CoC services use. To improve and preserve continuity of care, it is critical to leverage every maternal health facility encounter to encourage sustained service usage at each step of the continuum. Government policies should prioritise women's empowerment and raise public awareness of maternity services.

Spatial epidemiological characteristics and driving factors of myopia among school-age children based on geographical detector: a national study

The present study aimed to examine the spatial characteristics of myopia and identify the socioeconomic and environmental factors influencing its prevalence. Myopia prevalence among children of school age of Han ethnicity in China was 56.6% in 2019, with the highest and lowest prevalence's in Shandong (66.8%) and Guizhou (47.3%), respectively. There was a spatial aggregation of myopia prevalence in China. Environmental factors (atmospheric PM2.5 concentration and forest coverage) and socioeconomic factors (gross domestic product per capita, per capita disposable income, hospital beds per thousand people, and Engel coefficient) have significant influences on myopia prevalence. The interaction of each factor on myopia showed nonlinear enhancement. Myopia prevalence among children of school age was spatially clustered, and environmental and socioeconomic conditions are associated with myopia prevalence. Our findings provide novel perspectives for the comprehensive prevention and control of myopia.

Where does Aedes albopictus (Diptera: Culicidae) really breed in a Mediterranean residential area? Results from a field study in Valencia, Eastern Spain

Since its introduction in Spain in 2004, Aedes albopictus has rapidly spread across the country. Its aggressive biting behaviour causes nuisance, limiting outdoor activities. Also, its role as a vector of several arboviruses implies a major public health risk, with several cases of autochthonous dengue having been reported nationwide over the past few years. Control strategies usually focus on interventions in breeding sites. As such, accurate knowledge of the main larval habitats becomes a major priority in infested areas. A detailed identification of breeding sites of Ae. albopictus was carried out in the outdoors of 60 residential properties during July-August 2022 in El Vedat de Torrent (Valencia, Eastern Spain), an area recently colonised by this species. A total of 1444 real and potential breeding sites were examined. The most abundant potential larval habitat were plant pot plates (6.48 units/house), although a low infestation level was found, both for larvae (2.06% positivity, x̄ = 30.5 larvae/container), and pupae (0.51%, x̄ = 2.5 pupae/container). A total of 7715 larvae and 205 pupae were found in a disused flooded water pool depuration system. Animal drinkers, buckets and irrigation water containers were found to be the most common positive containers. No statistical difference was observed among the different container materials. A general statistical increase of 1 larva per 11.7 ml of water in breeding sites was detected. Breeding sites of other species such as Culex pipiens (n = 2) and Culex modestus (n = 1) were also rarely found in this residential area. To our knowledge, this is the first aedic index study carried out in Europe, and it provides valuable information about the main domestic breeding habitats of Ae. albopictus, which can greatly improve control programmes.

Spatiotemporal characteristics and influencing factors for joint events of air pollution wave and cold wave in China

Climate change triggered more environmental extremes. The joint events of air pollution wave and cold wave showed higher health risks than independent events, but little evidence is available for the spatiotemporal features of their co-occurrence. To better understand and forecast the joint events, a method framework was developed in this study. The temporal trend and spatial distribution of count and duration for joint events were measured at each grid cell (0.5°×0.5°) by integrating the PM2.5 air pollution wave and cold wave. The generalized linear mixed model was used to screen influencing variables that took into account socioeconomic characteristics, meteorological variables, and annual PM2.5 levels. During 2000 and 2018, the average annual count of joint events was 4.1 ± 6.8 days and the average duration ranged from 1.0 to 9.7 days. High spatial heterogeneity was observed throughout China, with a significant increase in joint events observed in Xinjiang area (the largest province in China). The most average count of joint events was observed in Henan province (one of the most populous provinces), while the longest duration was in Chongqing (a municipality, one of the megacities). Areas with higher PM2.5 levels, prolonged air pollution wave, and cold wave durations would experience more joint events. These findings can assist China in locating vulnerable areas and establishing effective local early warning systems. The method framework offers broader perspectives on mitigating health risks associated with extreme events in other countries and regions.

Epidemiological trends and sociodemographic factors associated with acute hemorrhagic conjunctivitis in mainland China from 2004 to 2018

BACKGROUND

Acute hemorrhagic conjunctivitis (AHC) is classified as a class C notifiable infectious disease in China and poses a great threat to public health. This study aimed to investigate the epidemiological trends and hotspots of AHC in mainland China. Sociodemographic factors that could contribute to early warning of AHC were further explored.

METHODS

Yearly and monthly incidences of acute hemorrhagic conjunctivitis by date and region from 2004 to 2018 were extracted from the Data Center of China Public Health Science. Joinpoint regression and spatial autocorrelation analysis were performed to explore the epidemiological trends and hotspots of AHC. A generalized linear model was then applied to explore the relationship between sociodemographic factors and AHC incidence.

RESULTS

The average annual AHC incidence was 3.58/100,000 in mainland China. The first-level spatial and temporal aggregation areas were distributed in Guangxi, Hainan, Guangdong, Guizhou, Hunan, Jiangxi, Fujian, Chongqing, Hubei, Anhui, and Zhejiang, with gathering times from 2010/1/1 to 2010/12/31 (RR = 20.13, LLR = 474,522.89, P < 0.01). After 2010, the AHC incidence was stable (APC = - 8.37, 95% CI: - 23.02-9.06). However, it was significantly increased in low- and middle-income provinces (AAPC = 10.65, 95% CI: 0.62-21.68, AAPC = 11.94, 95% CI: 0.62-24.53). The peak of AHC occurred during the August to October period. Children who age 0-3 years are identified as high-risk group with AHC incidence significantly increased (APC = 31.54, 95% CI: 0.27-72.56). Birth rate, population ages 0-14 (% of total population), passenger traffic, and urban population (% of total population) were positively associated with the AHC incidence, while per capita gross domestic product was negatively associated with the AHC incidence.

CONCLUSION

Overall, the AHC incidence was stable after 2010 in China, but it was significantly increased in low- and middle-income provinces. Regions with a high birth rate, population ages 0-14 (% of the total population), passenger traffic, urban population (% of the total population) and low per capita gross domestic product are at high risk of incidences of AHC. In the future, public health policy and resource priority for AHC in regions with these characteristics are necessary.

Epidemiological Trends and Hotspots of Other Infectious Diarrhea (OID) in Mainland China: A Population-Based Surveillance Study From 2004 to 2017

Background: The incidence of other infectious diarrhea (OID) ranked second in class C notifiable disease in China. It has posed a great threat to public health of all age groups. The aim of this study was to investigate the epidemiological trends and hotspots of OID in mainland China. Materials and Methods: Incidence and mortality data for OID stratified by date, age and region from 2004 to 2017 was extracted from the data-center of China public health science. Joinpoint regression and space-time analyses were performed to explore the epidemiological trends and hotspots of OID. Results: The average annual incidence of OID was 60.64/100,000 and it showed an increased trend in the mainland China especially after 2006 (APC = 4.12, 95 CI%: 2.06-6.21). Children of 0-4 year age group accounts for 60.00% (5,820,897/11,414,247) of all cases and its incidence continuously increased though 2004-2017 (APC = 6.65, 95 CI%: 4.39-8.96). The first-level spatial and temporal aggregation areas were located in Beijing and Tianjin, with the gathering time from 2005/1/1 to 2011/12/31 (RR = 5.52, LLR = 572893.59, P < 0.001). The secondary spatial and temporal aggregation areas covered Guangdong, Guangxi, Hainan and Guizhou from 2011/1/1 to 2017/12/31 (RR = 1.98, LLR = 242292.72, P < 0.001). OID of Tianjin and Beijing presented a decreased trend since 2006. However, the incidence of OID in Guangdong, Guangxi, Hainan and Guizhou showed increased trends through 2004-2017. Conclusion: Our study showed that OID showed a constantly increasing trend and brought considerable burden in China especially in the 0-4 age group. The high-risk periods and clusters of regions for OID were identified, which will help government develop disease-specific and location-specific interventive measures.

Women's cancers in China: a spatio-temporal epidemiology analysis

BACKGROUND

Women's cancers, represented by breast and gynecologic cancers, are emerging as a significant threat to women's health, while previous studies paid little attention to the spatial distribution of women's cancers. This study aims to conduct a spatio-temporal epidemiology analysis on breast, cervical and ovarian cancers in China, thus visualizing and comparing their epidemiologic trends and spatio-temporal changing patterns.

METHODS

Data on the incidence and mortality of women's cancers between January 2010 and December 2015 were obtained from the National Cancer Registry Annual Report. Linear tests and bar charts were used to visualize and compare the epidemiologic trends. Two complementary spatial statistics (Moran's I statistics and Kulldorff's space-time scan statistics) were adopted to identify the spatial-temporal clusters.

RESULTS

The results showed that the incidence and mortality of breast cancer displayed slow upward trends, while that of cervical cancer increase dramatically, and the mortality of ovarian cancer also showed a fast increasing trend. Significant differences were detected in incidence and mortality of breast, cervical and ovarian cancer across east, central and west China. The average incidence of breast cancer displayed a high-high cluster feature in part of north and east China, and the opposite traits occurred in southwest China. In the meantime, the average incidence and mortality of cervical cancer in central China revealed a high-high cluster feature, and that of ovarian cancer in northern China displayed a high-high cluster feature. Besides, the anomalous clusters were also detected based on the space-time scan statistics.

CONCLUSION

Regional differences were detected in the distribution of women's cancers in China. An effective response requires a package of coordinated actions that vary across localities regarding the spatio-temporal epidemics and local conditions.

Spatio-Temporal Patterns of Dengue Incidence in Medan City, North Sumatera, Indonesia

Dengue has been a perennial public health problem in Medan city, North Sumatera, despite the widespread implementation of dengue control. Understanding the spatial and temporal pattern of dengue is critical for effective implementation of dengue control strategies. This study aimed to characterize the epidemiology and spatio-temporal patterns of dengue in Medan City, Indonesia. Data on dengue incidence were obtained from January 2016 to December 2019. Kulldorff’s space-time scan statistic was used to identify dengue clusters. The Getis-Ord Gi* and Anselin Local Moran’s I statistics were used for further characterisation of dengue hotspots and cold spots. Results: A total of 5556 cases were reported from 151 villages across 21 districts in Medan City. Annual incidence in villages varied from zero to 439.32 per 100,000 inhabitants. According to Kulldorf’s space-time scan statistic, the most likely cluster was located in 27 villages in the south-west of Medan between January 2016 and February 2017, with a relative risk (RR) of 2.47. Getis-Ord Gi^* and LISA statistics also identified these villages as hotpot areas. Significant space-time dengue clusters were identified during the study period. These clusters could be prioritized for resource allocation for more efficient prevention and control of dengue.

Optimization of convolutional neural network hyperparameters for automatic classification of adult mosquitoes

The economic and social impacts due to diseases transmitted by mosquitoes in the latest years have been significant. Currently, no specific treatment or commercial vaccine exists for the control and prevention of arboviruses, thereby making entomological characterization fundamental in combating diseases such as dengue, chikungunya, and Zika. The morphological identification of mosquitos includes a visual exam of the samples. It is time consuming and requires adequately trained professionals. Accordingly, the development of a new automated method for realizing mosquito-perception and -classification is becoming increasingly essential. Therefore, in this study, a computational model based on a convolutional neural network (CNN) was developed to extract features from the images of mosquitoes and then classify the species Aedes aegypti, Aedes albopictus, and Culex quinquefasciatus. In addition, the model was trained to detect the mosquitoes of the genus Aedes. To train CNNs to perform the automatic morphological classification of mosquitoes, a dataset, which included 7,561 images of the target mosquitoes and 1,187 images of other insects, was acquired. Various neural networks, such as Xception and DenseNet, were used for developing the automatic-classification model based on images. A structured optimization process of random search and grid search was developed to select the hyperparameters set and increase the accuracy of the model. In addition, strategies to eliminate overfitting were implemented to increase the generalization of the model. The optimized model, during the test phase, obtained the balanced accuracy (BA) of 93.5% in classifying the target mosquitoes and other insects and the BA of 97.3% in detecting the mosquitoes of the genus Aedes in comparison to Culex. The results provide fundamental information for performing the automatic morphological classification of mosquito species. Using a CNN-embedded entomological tool is a valuable and accessible resource for health workers and non-taxonomists for identifying insects that can transmit infectious diseases.

Notifiable Respiratory Infectious Diseases in China: A Spatial-Temporal Epidemiology Analysis

Nowadays, tuberculosis, scarlet fever, measles, influenza, and mumps are five major notifiable respiratory infectious diseases (RIDs) in China. The objective of this study was to describe, visualize, and compare the spatial-temporal distributions of these five RIDs from 2006 to 2016. In addition to descriptive epidemiology analysis, seasonality and spatial autocorrelation analysis were also applied to explore the epidemiologic trends and spatial changing patterns of the five RIDs, respectively. The results indicated that the incidence of tuberculosis, measles, and mumps presented a downtrend trend, while those of scarlet fever and influenza was in a strong uptrend across the research period. The incidences of the five diseases all peaked in spring. There were significant spatial disparities in the distribution of tuberculosis, scarlet fever, and measles cases, with the hotspots mainly located in the western plateau region, northern plain region, and southern mountainous region. To conclude, notable epidemiological differences were observed across regions, indicating that some provincial units should pay more attention to prevent and control respiratory infectious diseases.

Detecting the priority areas for health workforce allocation with LISA functions: an empirical analysis for China

Background

Health workforce misdistribution leads to severe inequity and low-efficiency in health services in the developing countries. Targeting at China, this research aims to reveal, visualize and compare the geographical distribution patterns of different subtypes of urban and rural health workforce and identify the priority regions for health workforce planning and allocation policies designing.

Methods

The health workforce density (workforce-to-population ratio) is adopted to represent the accessibility to health workforce in each geographical unit. Besides a descriptive geography of health workforce as a whole, the local indicators of spatial association (LISA) are used to explore the spatial clusters of different subtypes of health workforce, which are visualized by geographical tools.

Results

Results reveal that regional disparities and spatial clusters exist in China’s health workforce distribution, with different types of workforce exhibiting relatively different spatial distribution characteristics. Besides, huge urban-rural disparities are found in the distribution of health workforce in China. Unexpectedly but intriguingly, most of the high-high and high-low cluster area of urban health workforce are concentrated in the western China (Xinjiang, Xizang etc.), indicating the relative abundant stock of urban health workforce in these units, while the low-low and low-high cluster area of different types of urban health workforce are mainly distributed in middle China. Regarding the rural health workforce, there is an obvious and similar low-low and low-high clustering pattern in western provinces (Sichuan, Yunnan) for the licensed doctors, pharmacists, technologists, which play a critical role in health services delivery.

Conclusions

Different types of health workforce displayed distinct spatial distribution patterns, while the misdistribution of rural health workforce imposed more challenges to the Chinese health sector due to its poorer stock and more disadvantaged positions of backward regions (i.e., low-low and low-high cluster area). Subtype-specific and region-oriented health workforce planning and allocation policies are suggested to be made, aiming at the urban and rural health workforce respectively, by prioritizing the identified low-low and low-high cluster areas.

Electronic supplementary material

The online version of this article (10.1186/s12913-018-3737-y) contains supplementary material, which is available to authorized users.

Inner Mongolia: A Potential Portal for the Spread of Rabies to Western China

In recent years, the number of human rabies cases in China has decreased annually. However, some western provinces with no human cases for more than 10 years have begun to report rabies cases, and all of the rabies lineages that circulated in western China were found in Inner Mongolia as well. In this study, we generated a phylogenetic tree with all the Inner Mongolia rabies strains available in GenBank and our laboratory, as well as strains from western China and representative viruses from neighboring countries, based on the N gene sequence. Furthermore, the possible relationships underlying the spread of the virus within Inner Mongolia and neighboring regions were analyzed. Three of six rabies lineages of China (China I-VI) were shown to exist in Inner Mongolia, and a spatial cluster analysis supported that the China I lineage, the dominant cluster of China, likely spread to Ningxia from Inner Mongolia. Wild raccoon dog rabies (China IV/Arctic-like-2) may have spread to Inner Mongolia from Russia and likely continued to spread to Qinghai and Tibet. The red fox lineage (China III/Cosmopolitan), which likely spread from Russia and Mongolia, has been shown to circulate in Inner Mongolia and was a serious threat to Xinjiang, which is adjacent to Inner Mongolia. Thus, Inner Mongolia likely became a location where national and international rabies viruses collected and developed into a potential portal for the spread of rabies to western China. To effectively control the spread of rabies in China, both prevention and control of dog and wild animal rabies in Inner Mongolia should be a top priority.

Spatial distribution of 12 class B notifiable infectious diseases in China: A retrospective study

BACKGROUND

China is the largest developing country with a relatively developed public health system. To further prevent and eliminate the spread of infectious diseases, China has listed 39 notifiable infectious diseases characterized by wide prevalence or great harm, and classified them into classes A, B, and C, with severity decreasing across classes. Class A diseases have been almost eradicated in China, thus making class B diseases a priority in infectious disease prevention and control. In this retrospective study, we analyze the spatial distribution patterns of 12 class B notifiable infectious diseases that remain active all over China.

METHODS

Global and local Moran's I and corresponding graphic tools are adopted to explore and visualize the global and local spatial distribution of the incidence of the selected epidemics, respectively. Inter-correlations of clustering patterns of each pair of diseases and a cumulative summary of the high/low cluster frequency of the provincial units are also provided by means of figures and maps.

RESULTS

Of the 12 most commonly notifiable class B infectious diseases, viral hepatitis and tuberculosis show high incidence rates and account for more than half of the reported cases. Almost all the diseases, except pertussis, exhibit positive spatial autocorrelation at the provincial level. All diseases feature varying spatial concentrations. Nevertheless, associations exist between spatial distribution patterns, with some provincial units displaying the same type of cluster features for two or more infectious diseases. Overall, high-low (unit with high incidence surrounded by units with high incidence, the same below) and high-high spatial cluster areas tend to be prevalent in the provincial units located in western and southwest China, whereas low-low and low-high spatial cluster areas abound in provincial units in north and east China.

CONCLUSION

Despite the various distribution patterns of 12 class B notifiable infectious diseases, certain similarities between their spatial distributions are present. Substantial evidence is available to support disease-specific, location-specific, and disease-combined interventions. Regarding provinces that show high-high/high-low patterns of multiple diseases, comprehensive interventions targeting different diseases should be established. As to the adjacent provincial units revealing similar patterns, coordinated actions need to be taken across borders.