The epidemiological characteristics of dengue in high-risk areas of China, 2013–2016

Introduction Dengue has become a more serious human health concern in China, with increased incidence and expanded outbreak regions. The knowledge of the cross-sectional and longitudinal epidemiological characteristics and the evolutionary dynamics of dengue in high-risk areas of China is limited. Methods Records of dengue cases from 2013 to 2016 were obtained from the China Notifiable Disease Surveillance System. Full envelope gene sequences of dengue viruses detected from the high-risk areas of China were collected. Maximum Likelihood tree and haplotype network analyses were conducted to explore the phylogenetic relationship of viruses from high-risk areas of China. Results A total of 56,520 cases was reported in China from 2013 to 2016. During this time, Yunnan, Guangdong and Fujian provinces were the high-risk areas. Imported cases occurred almost year-round, and were mainly introduced from Southeast Asia. The first indigenous case usually occurred in June to August, and the last one occurred before December in Yunnan and Fujian provinces but in December in Guangdong Province. Seven genotypes of DENV 1–3 were detected in the high-risk areas, with DENV 1-I the main genotype and DENV 2-Cosmopolitan the secondary one. The Maximum Likelihood trees show that almost all the indigenous viruses separated into different clusters. DENV 1-I viruses were found to be clustered in Guangdong Province, but not in Fujian and Yunnan, from 2013 to 2015. The ancestors of the Guangdong viruses in the cluster in 2013 and 2014 were most closely related to strains from Thailand or Singapore, and the Guangdong virus in 2015 was most closely related to the Guangdong virus of 2014. Based on closest phylogenetic relationships, viruses from Myanmar possibly initiated further indigenous cases in Yunnan, those from Indonesia in Fujian, while viruses from Thailand, Malaysia, Singapore and Indonesia were predominant in Guangdong Province. Conclusions Dengue is still an imported disease in China, although some genotypes continued to circulate in successive years. Viral phylogenies based on the envelope gene suggested periodic introductions of dengue strains into China, primarily from Southeast Asia, with occasional sustained, multi-year transmission in some regions of China.

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Spatial-time Visualization of Cutaneous Leishmaniasis in an Urban Area: Informing Health Policy and Practice

10.21203/rs.3.rs-125091/v1 ◽

2020 ◽

Author(s):

Neda Firouraghi ◽

Sayyed Mostafa Mostafavi ◽

Amene Raouf-Rahmati ◽

Alireza Mohammadi ◽

Reza Saemi ◽

...

Keyword(s):

High Risk ◽

Incidence Rate ◽

Urban Area ◽

Incidence Rates ◽

Low Risk ◽

Health Concern ◽

Surveillance Systems ◽

Cross Sectional ◽

Targeted Interventions ◽

Risk Areas

Abstract Background:Cutaneous leishmaniasis (CL) is an important public health concern worldwide. Iran is among the most CL-affected countries, being listed as one of the first six endemic countries in the world. In order to develop targeted interventions, we performed a spatial-time visualization of CL cases in an urban area to identify high-risk and low-risk areas during 2016-2019.Methods:This cross-sectional study was conducted in the city of Mashhad. Patient data were gathered from Mashhad health centers. All cases (n=2425) were diagnosed in two stages; the initial diagnosis was based on clinical findings. Subsequently, clinical manifestation was confirmed by parasitological tests. The data were aggregated at the neighborhood and district levels and smoothed CL incidence rates per 100,000 individuals were calculated using the spatial empirical Bayesian approach. Furthermore, we used the Anselin Local Moran’s I statistic to identify clusters and outliers of CL distribution during 2016-2019 in Mashhad. Results:The overall incidence rates decreased from 34.6 per 100,000 in 2016 to 19.9 per 100,000 individuals in 2019. Both cluster analyses by crude incidence rate and smoothed incidence rate identified high-risk areas in southwestern Mashhad over the study period. Furthermore, the analyses revealed low-risk areas in northeastern Mashhad over the same 3-year period.Conclusions:The southwestern area of Mashhad had the highest CL incidence rates. This piece of information might be of value to design tailored interventions such as running effective resource allocation models, informed control plans and implementation of efficient surveillance systems. Furthermore, this study generates new hypotheses to test potential relationships between socio-economic and environmental risk factors and incidence of CL in areas with higher associated risks.

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On the Risk Assessment of Terrorist Attacks Coupled with Multi-Source Factors

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi7090354 ◽

2018 ◽

Vol 7 (9) ◽

pp. 354 ◽

Cited By ~ 3

Author(s):

Xun Zhang ◽

Min Jin ◽

Jingying Fu ◽

Mengmeng Hao ◽

Chongchong Yu ◽

...

Keyword(s):

Risk Assessment ◽

High Risk ◽

Southeast Asia ◽

The Philippines ◽

Assessment Model ◽

Terrorist Attacks ◽

Recommendation Algorithm ◽

Spatial Risk ◽

Risk Areas ◽

F Measure

Terrorism has wreaked havoc on today’s society and people. The discovery of the regularity of terrorist attacks is of great significance to the global counterterrorism strategy. In this study, we improve the traditional location recommendation algorithm coupled with multi-source factors and spatial characteristics. We used the data of terrorist attacks in Southeast Asia from 1970 to 2016, and comprehensively considered 17 influencing factors, including socioeconomic and natural resource factors. The improved recommendation algorithm is used to build a spatial risk assessment model of terrorist attacks, and the effectiveness is tested. The model trained in this study is tested with precision, recall, and F-Measure. The results show that, when the threshold is 0.4, the precision is as high as 88%, and the F-Measure is the highest. We assess the spatial risk of the terrorist attacks in Southeast Asia through experiments. It can be seen that the southernmost part of the Indochina peninsula and the Philippines are high-risk areas and that the medium-risk and high-risk areas are mainly distributed in the coastal areas. Therefore, future anti-terrorism measures should pay more attention to these areas.

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Myocardial Infarction Iincidence at the Northwest of Iran 2014–2018: A Spatial Analysis

10.21203/rs.3.rs-489173/v1 ◽

2021 ◽

Author(s):

Mohsen Soleimani ◽

Nasser Bagheri

Keyword(s):

Spatial Analysis ◽

High Risk ◽

Incidence Rate ◽

Rural Areas ◽

Disease Incidence ◽

Unmet Need ◽

Health Concern ◽

Local Health ◽

Hotspot Analysis ◽

Risk Areas

Abstract BackgroundMyocardial Infarction (MI) is a major important public health concern and has huge burden on health system across the world. This study aimed to explore the spatial variation of MI incidence and investigate if there is a spatial clusters in the MI patterns among rural areas in Zanjan province, Iran.Materials & MethodsThis was a retrospective and geospatial analysis study using MI incidence data from 2014-2018 from nine hospital information system databases. Three different spatial analysis methods (Spatial autocorrelation, hotspot analysis and cluster and outlier analysis) were used to identify potential clusters and high-risk areas of MI incidence at the study area.Results3,820 patients were registered at Zanjan hospitals due to MI during 2014-2018. The age-adjusted incidence rate of MI was 343 cases per 100,000 person which raised from 88 cases in 2014 to 114 cases in 2018 per 100,000 person (a 30% increase, P<0.001). Golabar region had the highest incidence rate of MI (515 cases per 100,000 person). Five hotspot and one high-high cluster were detected using spatial analysis methods.ConclusionThis showed that there is a great deal of spatial variations in the pattern of MI incidence in Zanjan province. The high incidence rate of MI in the study area compared to the national average, is a warning to local health authorities to determine the possible causes of disease incidence and potential drivers of high-risk areas. The spatial cluster analysis provided new evidence for policy-makers to design tailored interventions to reduce MI incidence and allocate health resource to unmet need areas.

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Spatial-temporal analysis of head injuries at the northwest of Iran 2014–2018

10.21203/rs.3.rs-571444/v1 ◽

2021 ◽

Author(s):

Mohsen Soleimani ◽

Ahmad Jalilvand ◽

Nasser Bagheri ◽

Roghayeh Soleimani

Keyword(s):

Spatial Analysis ◽

High Risk ◽

Incidence Rate ◽

Head Injuries ◽

Health Concern ◽

Injury Incidence ◽

Risk Areas ◽

Adjusted Incidence Rate ◽

Northwest Of Iran ◽

Adjusted Incidence

Abstract Background: head injuries (HI) are considered as a major public health concern across the world. This study aims to explore the incidence rate and spatial distribution of HI incidence at rural district levels in Zanjan province, Iran from 2014-2018.Materials & Methods: This study was a cross-sectional and geospatial analysis of head injury incidence pattern in rural areas at Zanjan province, Iran. Data were collected from nine hospital information system databases. Age-adjusted incidence rate and three different spatial analysis methods (Spatial autocorrelation, hotspot analysis and Anselin Local Moran's I) were used to detect the potential high-risk areas of HI incidence in the study area.Results: 4562 patients were registered at Zanjan hospitals due to HI from 2014-2018. The age-adjusted incidence rate of HI was 429 cases (95% CI, 418,443) per 100,000 person which increased from 74 cases in 2014 to 86 cases in 2018, (an 18% increase, P<0001). The highest incidence rate observed among men (80%, P<0001) and at the age group of 15-29 (44.4%, P<0001). Qarabolagh region had the highest incidence rate and five hotspot, seven coldspot, two high-high cluster and seven low-low cluster of HI incidence were detected using spatial analysis.Conclusion: This study provided an overview about the incidence rate and spatial pattern of HI incidence at finer geographical level at the northwest of Iran. This study detected high-risk areas and also showed a significant relationship between HI, geographical areas and genders, which can provide useful information for local health authorities to apply prevention programs for reducing the burden of HI in the society.

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Geographical distribution of risk factors for invasive non-typhoidal Salmonella at the subnational boundary level in sub-Saharan Africa

BMC Infectious Diseases ◽

10.1186/s12879-021-06198-1 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Jung-Seok Lee ◽

Vittal Mogasale ◽

Florian Marks ◽

Jerome Kim

Keyword(s):

Risk Factors ◽

High Risk ◽

Case Fatality ◽

Population Based ◽

Sub Saharan Africa ◽

Health Concern ◽

Risk Level ◽

Accurate Estimation ◽

Risk Areas ◽

Sub Saharan

Abstract Background Invasive non-typhoidal Salmonella (iNTS) is a growing health-concern in many parts of sub-Saharan Africa. iNTS is associated with fatal diseases such as HIV and malaria. Despite high case fatality rates, the disease has not been given much attention. The limited number of population-based surveillance studies hampers accurate estimation of global disease burden. Given the lack of available evidence on the disease, it is critical to identify high risk areas for future surveillance and to improve our understanding of iNTS endemicity. Methods Considering that population-based surveillance data were sparse, a composite index called the iNTS risk factor (iNRF) index was constructed based on risk factors that commonly exist across countries. Four risk factors associated with the prevalence of iNTS were considered: malaria, HIV, malnutrition, and safe water. The iNRF index was first generated based on the four risk factors which were collected within a 50 km radius of existing surveillance sites. Pearson product-moment correlation was used to test statistical associations between the iNRF index and the prevalence of iNTS observed in the surveillance sites. The index was then further estimated at the subnational boundary level across selected countries and used to identify high risk areas for iNTS. Results While the iNRF index in some countries was generally low (i.e. Rwanda) or high (i.e. Cote d’Ivoire), the risk-level of iNTS was variable not only by country but also within a country. At the provincial-level, the highest risk area was identified in Maniema, the Democratic Republic of Congo, whereas Dakar in Senegal was at the lowest risk. Conclusions The iNRF index can be a useful tool to understand the geographically varying risk-level of iNTS. Given that conducting a population-based surveillance study requires extensive human and financial resources, identifying high risk areas for iNTS prior to a study implementation can facilitate an appropriate site-selection process in the future.

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LINC-28. EPIDEMIOLOGICAL CHARACTERISTICS AND SURVIVAL OUTCOMES OF CHILDREN WITH MEDULLOBLASTOMA TREATED AT THE NATIONAL CANCER INSTITUTE (INCA) IN RIO DE JANEIRO, BRAZIL

Neuro-Oncology ◽

10.1093/neuonc/noaa222.462 ◽

2020 ◽

Vol 22 (Supplement_3) ◽

pp. iii383-iii384

Author(s):

Gabriela Oigman ◽

Diana Osorio ◽

Joseph Stanek ◽

Jonathan Finlay ◽

Denizar Vianna ◽

...

Keyword(s):

High Risk ◽

Maternal Education ◽

Survival Outcomes ◽

Middle Income ◽

Female Ratio ◽

High Risk Patients ◽

Presenting Symptoms ◽

Risk Patients ◽

Epidemiological Characteristics ◽

Standard Risk

Abstract BACKGROUND Medulloblastoma (MB), the most malignant brain tumor of childhood has survival outcomes exceeding 80% for standard risk and 60% for high risk patients in high-income countries (HIC). These results have not been replicated in low-to-middle income countries (LMIC), where 80% of children with cancer live. Brazil is an upper-middle income country according to World Bank, with features of LMIC and HIC. METHODS We conducted a retrospective review of 126 children (0–18 years) diagnosed with MB from 1997 to 2016 at INCA. Data on patients, disease characteristics and treatment information were retrieved from the charts and summarized descriptively; overall survival (OS) and event-free survival (EFS) were calculated using the Kaplan-Meier Method. RESULTS The male/female ratio was 1.42 and the median age at diagnosis was 7.9 years. Headache (79%) and nausea/vomiting (75%) were the most common presenting symptoms. The median time from onset of symptoms to surgery was 50 days. The OS for standard-risk patients was 69% and 53% for high-risk patients. Patients initiating radiation therapy within 42 days after surgery (70.6% versus 59.6% p=0.016) experienced better OS. Forty-five patients (35%) had metastatic disease at admission. Lower maternal education correlated with lower OS (71.3% versus 49% p=0.025). Patients who lived >40km from INCA fared better (OS= 68.2% versus 51.1% p=0.032). Almost 20% of families lived below the Brazilian minimum wage. CONCLUSIONS These findings suggest that socioeconomic factors, education, early diagnosis and continuous data collection, besides oncological treatment must be adressed to improve the survival of children with MB.

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An Alternative Risk Assessment Model of Urban Waterlogging: A Case Study of Ningbo City

Sustainability ◽

10.3390/su13020826 ◽

2021 ◽

Vol 13 (2) ◽

pp. 826

Author(s):

Meiling Zhou ◽

Xiuli Feng ◽

Kaikai Liu ◽

Chi Zhang ◽

Lijian Xie ◽

...

Keyword(s):

Risk Assessment ◽

High Risk ◽

Assessment Model ◽

Risk Assessments ◽

Risk Assessment Model ◽

Risk Area ◽

The North ◽

Coastal Cities ◽

Risk Areas ◽

The City

Influenced by climate change, extreme weather events occur frequently, and bring huge impacts to urban areas, including urban waterlogging. Conducting risk assessments of urban waterlogging is a critical step to diagnose problems, improve infrastructure and achieve sustainable development facing extreme weathers. This study takes Ningbo, a typical coastal city in the Yangtze River Delta, as an example to conduct a risk assessment of urban waterlogging with high-resolution remote sensing images and high-precision digital elevation models to further analyze the spatial distribution characteristics of waterlogging risk. Results indicate that waterlogging risk in the city proper of Ningbo is mainly low risk, accounting for 36.9%. The higher-risk and medium-risk areas have the same proportions, accounting for 18.7%. They are followed by the lower-risk and high-risk areas, accounting for 15.5% and 9.6%, respectively. In terms of space, waterlogging risk in the city proper of Ningbo is high in the south and low in the north. The high-risk area is mainly located to the west of Jiangdong district and the middle of Haishu district. The low-risk area is mainly distributed in the north of Jiangbei district. These results are consistent with the historical situation of waterlogging in Ningbo, which prove the effectiveness of the risk assessment model and provide an important reference for the government to prevent and mitigate waterlogging. The optimized risk assessment model is also of importance for waterlogging risk assessments in coastal cities. Based on this model, the waterlogging risk of coastal cities can be quickly assessed, combining with local characteristics, which will help improve the city’s capability of responding to waterlogging disasters and reduce socio-economic loss.

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Modelling local patterns of child mortality risk: a Bayesian Spatio-temporal analysis

BMC Public Health ◽

10.1186/s12889-020-10016-9 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Alejandro Lome-Hurtado ◽

Jacques Lartigue-Mendoza ◽

Juan C. Trujillo

Keyword(s):

High Risk ◽

Mexico City ◽

Child Mortality ◽

Mortality Risk ◽

Temporal Analysis ◽

Health Concern ◽

The North ◽

Greater Mexico ◽

Spatio Temporal ◽

Child Mortality Rate

Abstract Background Globally, child mortality rate has remained high over the years, but the figure can be reduced through proper implementation of spatially-targeted public health policies. Due to its alarming rate in comparison to North American standards, child mortality is particularly a health concern in Mexico. Despite this fact, there remains a dearth of studies that address its spatio-temporal identification in the country. The aims of this study are i) to model the evolution of child mortality risk at the municipality level in Greater Mexico City, (ii) to identify municipalities with high, medium, and low risk over time, and (iii) using municipality trends, to ascertain potential high-risk municipalities. Methods In order to control for the space-time patterns of data, the study performs a Bayesian spatio-temporal analysis. This methodology permits the modelling of the geographical variation of child mortality risk across municipalities, within the studied time span. Results The analysis shows that most of the high-risk municipalities were in the east, along with a few in the north and west areas of Greater Mexico City. In some of them, it is possible to distinguish an increasing trend in child mortality risk. The outcomes highlight municipalities currently presenting a medium risk but liable to become high risk, given their trend, after the studied period. Finally, the likelihood of child mortality risk illustrates an overall decreasing tendency throughout the 7-year studied period. Conclusions The identification of high-risk municipalities and risk trends may provide a useful input for policymakers seeking to reduce the incidence of child mortality. The results provide evidence that supports the use of geographical targeting in policy interventions.

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Epidemiological profile of Plasmodium ovale spp. imported from Africa to Anhui Province, China, 2012–2019

Malaria Journal ◽

10.1186/s12936-020-03551-8 ◽

2021 ◽

Vol 20 (1) ◽

Author(s):

Tao Zhang ◽

Shuqi Wang ◽

Duoquan Wang ◽

Sarah Auburn ◽

Shenning Lu ◽

...

Keyword(s):

Information System ◽

Disease Control ◽

Latency Period ◽

Anhui Province ◽

Detection Methods ◽

Health Concern ◽

Plasmodium Ovale ◽

Control And Prevention ◽

Endemic Areas ◽

Epidemiological Characteristics

Abstract Background Although autochthonous malaria cases are no longer reported in Anhui Province, China, imported malaria has become a major health concern. The proportion of reported malaria cases caused by Plasmodium ovale spp. increased to levels higher than expected during 2012 to 2019, and showed two peaks, 19.69% in 2015 and 19.35% in 2018. Methods A case-based retrospective study was performed using data collected from the China Information System for Disease Control and Prevention (CISDCP) and Information System for Parasitic Disease Control and Prevention (ISPDCP) from 2012 to 2019 to assess the trends and differences between Plasmodium ovale curtisi (P. o. curtisi) and Plasmodium ovale wallikeri (P. o. wallikeri). Epidemiological characteristics were analyzed using descriptive statistics. Results Plasmodium o. curtisi and P. o. wallikeri were found to simultaneously circulate in 14 African countries. Among 128 patients infected with P. ovale spp., the proportion of co-infection cases was 10.16%. Six cases of co-infection with P. ovale spp. and P. falciparum were noted, each presenting with two clinical attacks (the first attack was due to P. falciparum and the second was due to P. ovale spp.) at different intervals. Accurate identification of the infecting species was achieved among only 20.00% of cases of P. ovale spp. infection. At the reporting units, 32.17% and 6.96% of cases of P. ovale spp. infection were misdiagnosed as P. vivax and P. falciparum infections, respectively. Conclusion The present results indicate that the potential of P. ovale spp. to co-infect with other Plasmodium species has been previously underestimated, as is the incidence of P. ovale spp. in countries where malaria is endemic. P. o. curtisi may have a long latency period of > 3 years and potentially cause residual foci, thus posing challenges to the elimination of malaria in P. ovale spp.-endemic areas. Considering the low rate of species identification, more sensitive point-of-care detection methods need to be developed for P. ovale spp. and introduced in non-endemic areas.

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Prevalence of small for gestational age infants in 21 cities in China, 2014–2019

Scientific Reports ◽

10.1038/s41598-021-87127-9 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Hui He ◽

Huazhang Miao ◽

Zhijiang Liang ◽

Ye Zhang ◽

Wei Jiang ◽

...

Keyword(s):

Gestational Age ◽

Small For Gestational Age ◽

Health Information System ◽

Guangdong Province ◽

Significant Negative Correlation ◽

Term Infants ◽

Per Capita Gdp ◽

Increased Risk ◽

Per Capita ◽

Epidemiological Characteristics

AbstractInfants who are small for gestational age (SGA) are at increased risk of neonatal and infant death, non-communicable diseases and growth retardation. However, the epidemiological characteristics of SGA remain unclear. We aim to explore the prevalence of SGA and to examine its socioeconomic associations by using data from 21 cities. 10,515,494 single live birth records between 2014 and 2019 from the Guangdong Women and Children Health Information System were included in the study. Descriptive statistical methods were used to analyze the prevalence trend of SGA and its distribution. We also analyze the associations between the prevalence of SGA and per-capita GDP. The prevalence of SGA in Guangdong Province from the years 2014–2019 was 13.17%, 12.96%, 11.96%, 12.72%, 11.45%, 11.30% respectively, and the overall prevalence was 12.28%. The prevalence of term SGA infants in Guangdong Province was 12.50%, which was much higher than that of preterm SGA (7.71%). There was a significant negative correlation between the SGA prevalence and per-capita GDP in 21 cities of Guangdong Province. The level of economic development may affect the prevalence of SGA. The prevalence of SGA in full term infants is significantly higher than in premature infants, suggesting that most SGA infants may be born at a later gestational age.

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