Identifying and characterizing hepatitis C virus hotspots in Massachusetts: a spatial epidemiological approach

Insights into the spatial epidemiology of hepatitis C infection: systematic synthesis of area-level determinants and spatiotemporal analyses

BACKGROUND

Hepatitis C virus (HCV) stands at the forefront of global elimination endeavors by 2030, highlighting the need for a nuanced exploration into disparities and vulnerabilities using innovative spatial epidemiological approaches. This study aimed to systematically review existing literature to summarize area-level factors associated with HCV infection and to examine the application of spatial and spatiotemporal analyses in HCV research.

METHODS

A systematic search following PRISMA guidelines was conducted for peer-reviewed literature published between 2000 and 2023 using PubMed, Web of Science, Scopus, and Embase databases. The synthesis of area-level factors was organized according to four distinct categories of risk environments: social, economic, policy, and physical environments.

RESULTS

Sixty-five studies were selected for this systematic review. 60% of the studies focused on the general population, while 20% of the studies targeted people who inject drugs. The area-level factors explored predominantly were characteristics of the social and economic risk environments. For instance, areas with a higher level of socioeconomic disadvantage, lower education attainment, higher population density, and located more remotely were associated with higher HCV infection rates. Additionally, some studies noted a significant correlation between the accessibility to harm reduction and healthcare services and HCV occurrence, testing, and treatment rates. Furthermore, spatial data exploration and cluster analysis methods were the predominant methods used to explore the nuanced spatial distribution of HCV infection.

CONCLUSION

This review emphasizes the imperative of deciphering the complex interplay of area-level factors in HCV infection dynamics. Understanding the potential risk environment landscape of HCV could facilitate identifying vulnerable areas and communities. Additionally, the limited application of spatial analytics in HCV research highlights the untapped potential, emphasizing the need for enhanced spatial techniques to pinpoint priority areas for intervention.

Spatiotemporal distribution characteristics and impact factors of hepatitis C in Chongqing, China, 2014-2020

OBJECTIVES

This study aimed to explore the spatial and temporal distribution of hepatitis C and its influencing factors in Chongqing, providing a scientific basis for the relevant departments to formulate targeted preventive measures for the high prevalence of hepatitis C in the region and population.

DESIGN

We collected data on hepatitis C cases in Chongqing (located in the southwest of China) from 2014 to 2020, and analysed the spatiotemporal heterogeneity of hepatitis C incidence in different populations and identified factors that might influence the incidence of hepatitis C by constructing a Bayesian spatiotemporal model.

SETTINGS

The study subjects included clinically diagnosed cases and confirmed cases of hepatitis C with current address in Chongqing and onset date between 1 January 2014 and 31 December 2020.

PARTICIPANTS

The study used aggregated data, including 33 900 clinically diagnosed cases and confirmed cases of hepatitis C.

RESULTS

From 2014 to 2020, the high-risk areas of hepatitis C were primarily concentrated in the main and new urban areas of Chongqing. In contrast, the low-risk areas were mainly found in southeast and northeast Chongqing. There was also an increasing trend in the risk of incidence in the low-risk areas. Analysis of different populations revealed that men aged 45-59 years had a higher risk of developing hepatitis C in the main urban area compared with other age groups. Additionally, the risk for this population group showed an increasing trend in the southeast and northeast of Chongqing as well as the main urban area. Among women, the rising trend of hepatitis C risk was stronger for those aged 30-44 years in southeast Chongqing and for those aged 45-59 years in northeast Chongqing compared with other age groups. The analysis of influencing factors found that gross domestic product per capita, population density and the proportion of tertiary industry were associated with an increased risk of hepatitis C.

CONCLUSIONS

High-risk areas for hepatitis C virus were mainly located in the main and new urban areas of Chongqing, where the male prime-age population was the focus of prevention and treatment. In the future, the relevant authorities should concentrate on high-risk areas and at the same time strengthen screening and serological surveys for hepatitis C in low-risk areas and various populations, and raise public awareness of prevention, so as to reduce the incidence of hepatitis C.

A Road Map to Hepatitis C Elimination: Yesterday, Today, and Tomorrow

There are an estimated 3.5 million people with hepatitis C virus (HCV) infection in the United States, resulting in 15 000 HCV-related deaths in 2019 and approximately $7 billion annually in healthcare costs. Although the United States had experienced declining incidence, since 2010 hepatitis C infections have rebounded. The history of HCV treatment can be seen as a series of scientific triumphs that should be celebrated as the accomplishments that they represent. But new treatments will only get us so far: Social determinants of health drive the majority of health outcomes. Without addressing the factors that impact the lives of our patients, we will fall short in the outcomes we seek. Public health systems, hospital networks, and governments must work more cohesively to eradicate hepatitis C. We have the tools, both biomedical and social. The end of hepatitis C depends on our willingness to make use of them.

Spatial-temporal analysis and spatial drivers of hepatitis-related deaths in 183 countries, 2000-2019

Hepatitis is the seventh leading cause of mortality worldwide and is the only communicable disease where mortality is increasing, yet the long-term spatial-temporal variation at global scale and its possible causes, i.e., drivers, remain unknown. Firstly, this study employed the measure of spatial autocorrelation, Moran's I, and the measure of local spatial cluster, Getis-Ord Gi*, to characterize the spatial variation of mortality due to hepatitis in 183 countries globally for years 2000, 2010, 2015 and 2019. Then, a novel spatial statistical method, named the Geographical Detector, was utilized to investigate eight possible influencing factors, i.e., risk factors, of the spatial-temporal variation of mortality due to hepatitis. The results showed significant disparities of hepatitis-related mortality rates among countries. Hot spots, representing locations with higher mortality rates, were consistently observed in Africa, East Asia, and Southeast Asia, while the cold spots, representing locations with lower mortality rates, were predominantly found in Europe and the Americas. Potential spatial drivers of hepatitis mortality, identified by geographical detector, include "health expenditure", "universal health coverage", and "per capita income". However, "hepatitis B immunization" and "total population" were not identified as significant spatial drivers for hepatitis mortality The findings highlighted the critical role of socioeconomic factors in the variations in hepatitis mortality, and pointed out relative importance of increasing health expenditure, per capita income, and improve universal health coverage on alleviating global hepatitis-related mortality.

Geographic variation in HCV treatment penetration among people who inject drugs in Baltimore, MD

We evaluated geographic heterogeneity in hepatitis C virus (HCV) treatment penetration among people who inject drug (PWID) across Baltimore, MD since the advent of direct-acting antivirals (DAAs) using space-time clusters of HCV viraemia. Using data from a community-based cohort of PWID, the AIDS Linked to the IntraVenous Experience (ALIVE) study, we identified space-time clusters with higher-than-expected rates of HCV viraemia between 2015 and 2019 using scan statistics. We used Poisson regression to identify covariates associated with HCV viraemia and used the regression-fitted values to detect adjusted space-time clusters of HCV viraemia in Baltimore city. Overall, in the cohort, HCV viraemia fell from 77% in 2015 to 64%, 49%, 39% and 36% from 2016 to 2019. In Baltimore city, the percentage of census tracts where prevalence of HCV viraemia was ≥85% dropped from 57% to 34%, 25%, 22% and 10% from 2015 to 2019. We identified two clusters of higher-than-expected HCV viraemia in the unadjusted analysis that lasted from 2015 to 2017 in East and West Baltimore and one adjusted cluster of HCV viraemia in West Baltimore from 2015 to 2016. Neither differences in age, sex, race, HIV status, nor neighbourhood deprivation were able to explain the significant space-time clusters. However, residing in a cluster with higher-than-expected viraemia was associated with age, sex, educational attainment and higher levels of neighbourhood deprivation. Nearly 4 years after DAAs became available, HCV treatment has penetrated all PWID communities across Baltimore city. While nearly all census tracts experienced improvements, change was more gradual in areas with higher levels of poverty.

Patient characteristics and neighborhood attributes associated with hepatitis C screening and positivity in Philadelphia

Among patients of an urban primary care network in Philadelphia with a universal hepatitis C virus (HCV) screening policy for patients born during 1945-1965, we examined whether being unscreened and HCV positivity were associated with attributes of the census tracts where patients resided, which we considered as proxies for social health determinants. For patients with at least one clinic visit between 2014 and mid-2017, we linked demographic and HCV screening information from electronic health records with metrics that described the census tracts where patients resided. We used generalized estimating equations to estimate adjusted relative risk ratios (aRRs) for being unscreened and HCV positive. Overall, 28% of 6,906 patients were unscreened. Black race, male gender, and residence in census tracts with relatively high levels of violent crime, low levels of educational attainment and household incomes, and evidence of residential segregation by Hispanic ethnicity were associated with lower aRRs for being unscreened. Among screened patients, 9% were HCV positive. Factors associated with lower risks of being unscreened were, in general, associated with higher HCV positivity. Attributes of census tracts where patients reside are probably less apparent to clinicians than patients' gender or race but might reflect unmeasured patient characteristics that affected screening practices, along with preconceptions regarding the likelihood of HCV infection based on prior screening observations or implicit biases. Approaching complete detection of HCV-infected people would be hastened by focusing on residents of census tracts with attributes associated with higher infection levels or, if known, higher infection levels directly.

Epidemiological Profile of a Human Hepatitis E Virus Outbreak in 2018, Chattogram, Bangladesh

Hepatitis E virus (HEV) is a waterborne zoonotic disease that can result in a high fatality rate in pregnant women and infants. In 2018, a large HEV outbreak emerged in Chattogram, Bangladesh, resulting in 2800 cases and a significant public health response to mitigate the transmission. While the source of the outbreak remained poorly understood, authorities suggested that possible risk factors for HEV infection included contamination of water supply, exacerbated by concurrent severe flooding events in the community. A cross-sectional study was conducted to investigate the distribution and risk factors for HEV seroprevalence between January and December 2018 in the Chattogram city area. A total of 505 blood samples were collected from symptomatic patients of 10 hospitals who met the case definition for an HEV infection. Standard ELISA tests were performed in all patients to identify anti-HEV antibodies. The size and location of HEV seroprevalence clusters within Chattogram were investigated using SaTScan. We investigated the association between risk of HEV infection and individual and environmentally lagged risk factors using Bernoulli generalised linear regression models. Our results indicate an overall HEV seroprevalence of 35% with significant variation according to sex, source of drinking water, and boiling of drinking water. A positive cross-correlation was found between HEV exposure and precipitation, modified normalised difference water index (MNDWI), and normalised difference vegetation index (NDVI). Our model indicated that risk of infection was associated with sex, age, source of drinking water, boiling of water, increased precipitation, and increased MNDWI. The results from this study indicate that source and boiling of drinking water and increased precipitation were critical drivers of the 2018 HEV outbreak. The communities at highest risk identified in our analyses should be targeted for investments in safe water infrastructure to reduce the likelihood of future HEV outbreaks in Chattogram.

Spatial epidemiology: An empirical framework for syndemics research

Syndemics framework describes two or more co-occurring epidemics that synergistically interact with each other and the complex structural social forces that sustain them leading to excess disease burden. The term syndemic was first used to describe the interaction between substance abuse, violence, and AIDS by Merrill Singer. A broader range of syndemic studies has since emerged describing the framework's applicability to other public health scenarios. With syndemic theory garnering significant attention, the focus is shifting towards developing robust empirical analytical approaches. Unfortunately, the complex nature of the disease-disease interactions nested within several social contexts complicates empirical analyses. In answering the call to analyze syndemics at the population level, we propose the use of spatial epidemiology as an empirical framework for syndemics research. Spatial epidemiology, which typically relies on geographic information systems (GIS) and statistics, is a discipline that studies spatial variations to understand the geographic landscape and the risk environment within which disease epidemics occur. GIS maps provide visualization aids to investigate the spatial distribution of disease outcomes, the associated social factors, and environmental exposures. Analytical inference, such as estimation of disease risks and identification of spatial disease clusters, can provide a detailed statistical view of spatial distributions of diseases. Spatial and spatiotemporal models can help us to understand, measure, and analyze disease syndemics as well as the social, biological, and structural factors associated with them in space and time. In this paper, we present a background on syndemics and spatial epidemiological theory and practice. We then present a case study focused on the HIV and HCV syndemic in West Virginia to provide an example of the use of GIS and spatial analytical methods. The concepts described in this paper can be considered to enhance understanding and analysis of other syndemics for which space-time data are available.

A Spatial Approach for Ending the Human Immunodeficiency Virus Epidemic for the United States-A DC Model

BACKGROUND

Mode of transmission-based hotspots is a smart approach to HIV mitigation, yet remains poorly evaluated and implemented in the United States. The primary aim was to identifying mode of transmission-based hotspots and populations at risk of lower viral suppression to assist in targeted planning and implementation of programs.

METHODS

We implemented spatial statistics to identify global-local hotspots and regression analysis to find populations at risk of lower viral suppression within hotspots. Data were obtained from the District of Columbia's (DC's) active surveillance system, which were geocoded based on current residence address.

RESULTS

The analysis identified 6001 HIV-positive men who have sex with men (MSM) and 6077 HIV-positive non-MSM (N = 12 078) living in DC at the end of 2018. The hotspots for MSM were central DC and non-MSM in south DC. Trends of viral suppression within MSM hotspots showed plateauing and, among non-MSM, showed decline. Regression analysis showed MSM aged 21-25 (RR: 3.199; 95% CI: 1.832-5.586) and not linked to care (8.592; 2.907-25.398) were at higher risk of being virally unsuppressed within the hotspots. For non-MSM we found those aged 12-18 (9.025; 3.314-2.581) and with unknown linkages (6.087; 3.346-13.848) were at higher risk of being virally unsuppressed within the hotspots.

CONCLUSIONS

Our analysis provides a model that may be used by other jurisdictions to identify areas of priority and plan treatment-adherence programs using surveillance data. Attaining viral suppression is crucial in reducing new diagnoses; a spatial approach can be an important tool in Ending the HIV Epidemic.

Geographic Core Areas of Coinfections in Washington, District of Columbia: Recommendations for Planning Prevention-Intervention to Mitigate Human Immunodeficiency Virus Burden

BACKGROUND

Research suggests that human immunodeficiency virus (HIV)-positive individuals with a sexually transmitted infection (STI) may be at increased risk of transmitting HIV to someone else through unprotected sex. The primary aim of the analysis is to identify the high-risk geographic areas of transmission of coinfections and factors that may be associated with poor outcomes of viral suppression within these higher-risk geographic areas, thus important in transmission prevention.

METHODS

We used surveillance data reported by all providers and laboratories in the District of Columbia (DC). Applied discrete Poisson scan model in SaTScan to identify the geographic areas. The relative risk (RR) for the scan statistic was calculated based on events inside the cluster, and P values evaluated statistical significance. We used multinomial logistical regression to explore care and demographical characteristics associated with being virally unsuppressed within and outside the geographic areas.

RESULTS

The coinfected areas (RR, >1; P < .001) were located in the tracts of central and southern DC. Black population (RR, 3.154 [95% confidence interval {CI}, 1.736-5.729]), age 13-19 years (RR, 4.598 [95% CI, 3.176-6.657]), repeat STIs (RR, 1.387 [95% CI, 1.096-1.754]), and not retained in care (RR, 2.546 [95% CI, 1.997-3.245]) were found to be at higher risk of being virally unsuppressed within the coinfected clusters. Those with unknown linkages were found to be at higher risk of being virally unsuppressed outside the coinfected clusters (RR, 5.162 [95% CI, 2.289-11.640]).

CONCLUSIONS

This is DC's first effort to identify the geographic core areas of coinfections and factors that may be sustaining them. These results will be used by the health department to plan for prevention-intervention strategies. This model be replicated by any local jurisdiction similar.

Spatial analysis of risk areas for the development of tuberculosis and treatment outcomes

OBJECTIVES

to identify risk clusters for the occurrence of tuberculosis and its treatment outcomes.

METHODS

ecological study, in a city in Maranhão, using data from the Notifiable Diseases Information System. Point density analysis and isotonic scanning techniques were used to identify areas with the highest occurrence of treatment outcomes and identify risk areas for possible tuberculosis cases.

RESULTS

most tuberculosis cases occurred in the male, adult, brown-skinned population. Also, most of the reported cases were classified as pulmonary and as new cases that progressed to a cure. The areas with the highest density of cure, death and abandonment are located in the central region of the city.

CONCLUSIONS

the central region of the urban area of the city, with high demographic density and poor sanitary and socioeconomic conditions, presented a greater cluster of tuberculosis cases.

High visibility of outdoor tobacco advertisements around health facilities in East Java, Indonesia: a geospatial analysis

BACKGROUND Indonesian tobacco control initiatives are minimal despite having the second-highest adult male smoking prevalence in the world, with less than 10% of districts/cities banning outdoor tobacco advertisements. This research aimed to provide evidence on the presence of outdoor tobacco advertisements near health facilities in Surabaya where there is no outdoor advertising ban. METHODS Data collection was carried out in Surabaya from October to November 2018. Data of government (public) and private health facilities were obtained from the city health office. Two spatial data analyses were carried out: a buffer analysis near the healthcare facilities and an advertisement hotspot analysis using ArcMap 10.6. RESULTS From 308 tobacco advertisements that were identified, there were billboards (63%), banners (31%), and videoboards (7%). Of 142 public and 1,242 private health facilities in Surabaya, 26% and 31% had advertisements within 300 m and 63% and 70% were within advertisement hotspots, respectively. Furthermore, 5% of advertisements were within 300 m from public health facilities and 21% of them were within 300 m from private health facilities. CONCLUSIONS Outdoor tobacco advertisements were widespread throughout the city, prominently around public and private health facilities.

The Dynamics of Infectious Diseases Associated With Injection Drug Use in Lawrence and Lowell, Massachusetts

Background

There are a wide variety of infectious complications of injection drug use. Understanding the trajectory of these complications might inform the development of an early warning system for human immunodeficiency virus (HIV) outbreaks that occur regularly among people who inject drugs (PWID).

Methods

A distributed lag Poisson regression model in the Bayesian setting was used to examine temporal patterns in the incidence of injection-associated infectious diseases and their association with HIV cases in Lawrence and Lowell, Massachusetts between 2005 and 2018.

Results

Current-month HIV counts are associated with fatal overdoses approximately 8 months prior, cases of infective endocarditis 10 months prior, and cases of skin and soft tissue infections and incision and drainage procedures associated with these infections 12 months prior.

Conclusions

Collecting data on these other complications associated with injection drug use by public health departments may be important to consider because these complications may serve as input to a sentinel system to trigger early intervention and avert potential outbreaks of HIV.

Coupling ITO3dE model and GIS for spatiotemporal evolution analysis of agricultural non-point source pollution risks in Chongqing in China

To determine the risk state distribution, risk level, and risk evolution situation of agricultural non-point source pollution (AGNPS), we built an ‘Input-Translate-Output’ three-dimensional evaluation (ITO3dE) model that involved 12 factors under the support of GIS and analyzed the spatiotemporal evolution characteristics of AGNPS risks from 2005 to 2015 in Chongqing by using GIS space matrix, kernel density analysis, and Getis-Ord Gi* analysis. Land use changes during the 10 years had a certain influence on the AGNPS risk. The risk values in 2005, 2010, and 2015 were in the ranges of 0.40–2.28, 0.41–2.57, and 0.41–2.28, respectively, with the main distribution regions being the western regions of Chongqing (Dazu, Jiangjin, etc.) and other counties such as Dianjiang, Liangping, Kaizhou, Wanzhou, and Zhongxian. The spatiotemporal transition matrix could well exhibit the risk transition situation, and the risks generally showed no changes over time. The proportions of ‘no-risk no-change’, ‘low-risk no-change’, and ‘medium-risk no-change’ were 10.86%, 33.42%, and 17.25%, respectively, accounting for 61.53% of the coverage area of Chongqing. The proportions of risk increase, risk decline, and risk fluctuation were 13.45%, 17.66%, and 7.36%, respectively. Kernel density analysis was suitable to explore high-risk gathering areas. The peak values of kernel density in the three periods were around 1110, suggesting that the maximum gathering degree of medium-risk pattern spots basically showed no changes, but the spatial positions of high-risk gathering areas somehow changed. Getis-Ord Gi* analysis was suitable to explore the relationships between hot and cold spots. Counties with high pollution risks were Yongchuan, Shapingba, Dianjiang, Liangping, northwestern Fengdu, and Zhongxian, while counties with low risks were Chengkou, Wuxi, Wushan, Pengshui, and Rongchang. High-value hot spot zones gradually dominated in the northeast of Chongqing, while low-value cold spot zones gradually dominated in the Midwest. Our results provide a scientific base for the development of strategies to prevent and control AGNPS in Chongqing.

Detecting Spatial Cores and Temporal Trends of Repeat STIs to Plan Pre-exposure Prophylaxis (PrEP) Scale-up in DC

BACKGROUND

Repeat sexually transmitted infections (STIs) in DC primarily results from untreated sexual partners. This analysis aims to identify high-risk areas and temporal trends of repeat STIs for pre-exposure prophylaxis scale-up and STI mitigation in DC.

METHODS

We identified repeat infections in the DC Department of Health STI and HIV data management systems, diagnosed from 2014 to 2018. The cases were geocoded and aggregated by census tracts. Poisson discrete scan statistic was implemented in SaTScan software to find clusters. Weighted moving average was used to compare temporal trends of repeat STIs. We used χ analysis to identify association with demographic variables.

RESULTS

We identified 8535 repeat STIs from 2014 to 2018. Of these, 61.84% were among men, most cases were among blacks (34.75%) and 47.45% represented gonorrhea cases. The high-risk spatial clusters were identified as those tracts that had relative risk (relative risk > 1; P-value < 0.001). We identified one significant radius of risk covering tracts of wards 7 and 8 and parts of wards 5 and 6. We spotted positive temporal trends in cluster 1 and outside the cluster. We found significant associations of repeat STIs with gender (χ = 317.27, P < 0.001), age (χ = 539.26, P < 0.001), HIV coinfections (χ = 352.06, P < 0.001), and year of diagnoses (χ = 1.5, P < 0.01).

CONCLUSIONS

Our findings indicate spatial disparities in DC for repeat STIs. This analysis is critical for pre-exposure prophylaxis planning, STI prevention strategies such as expedited partner therapies and condom distribution strategies in DC should prioritize the high-risk spatial cores.

Opioid initiation and injection transition in rural northern New England: A mixed-methods approach

BACKGROUND

In rural northern New England, located in the northeastern United States, the overdose epidemic has accelerated with the introduction of fentanyl. Opioid initiation and transition to opioid injection have been studied in urban settings. Little is known about opioid initiation and transition to injection drug use in rural northern New England.

METHODS

This mixed-methods study characterized opioid use and drug injection in 11 rural counties in Massachusetts, Vermont, and New Hampshire between 2018 and 2019. People who use drugs completed audio computer-assisted self-interview surveys on substance use and risk behaviors (n = 589) and shared personal narratives through in-depth interviews (n = 22). The objective of the current study is to describe initiation of opioid use and drug injection in rural northern New England.

RESULTS

Median age of first injection was 22 years (interquartile range 18-28 years). Key themes from in-depth interviews that led to initiating drug injection included normalization of drug use in families and communities, experiencing trauma, and abrupt discontinuation of an opioid prescription. Other factors that led to a transition to injecting included lower cost, increased effect/ rush, greater availability of heroin/ fentanyl, and faster relief of withdrawal symptoms with injection.

CONCLUSIONS

Trauma, normalization of drug use, over-prescribing of opioids, and abrupt discontinuation challenge people who use drugs in rural northern New England communities. Inadequate opioid tapering may increase transition to non-prescribed drug use. The extent and severity of traumatic experiences described highlights the importance of enhancing trauma-informed care in rural areas.

Using geo-spatial analysis for assessing the risk of hospital admissions due to community-acquired pneumonia in under-5 children and its association with socially vulnerable areas (Brazil)

Background

The concentration of under-5 child morbidity and mortality due to pneumonia in developing countries reflects the social inequities. This study aimed to map and assess the spatial risk for hospitalization due to Community-Acquired Pneumonia in children under 5 years of age and its association with vulnerable areas.

Methods

Ecological study in the city of Ribeirão Preto, state of São Paulo, Brazil. The study population consisted of hospitalized under-5 children, diagnosed with community-acquired pneumonia, in Ribeirão Preto-São Paulo-Brazil, from 2012 to 2013. Data were collected in different databases, by a trained team, between March 2012 and August 2013 and from the 2010 Demographic Census of the Brazilian Institute of Geography and Statistics. The 956 urban census tracts were considered as the units of analysis. The incidence of cases per 10,000 inhabitants was calculated by census tracts during the study period. For the identification of the spatial risk clusters, the Kernel density estimator and the Getis-Ord Gi* technique were performed. Generalized additive models were used to verify the association between areas with social vulnerability and the occurrence of childhood pneumonia.

Results

The study included 265 children under the age of five, hospitalized due to community-acquired pneumonia. A concentration of cases was identified in the regions with greater social vulnerability (low income, poor housing conditions and homelessness), as well as a lower occurrence of cases in the most developed and economically privileged area of the city. The majority of the children lived in territories served by traditional primary healthcare units, in which the health surveillance and family and community focus are limited. It is important to highlight that the tracts with the highest degrees of vulnerability, such as those identified as high vulnerability (urban) and very high vulnerability (subnormal urban clusters).

Conclusions

The results contribute to the comprehension of the social factors involved in child hospitalization due to pneumonia, based on the analysis of the spatial distribution. This approach revealed a strategic tool for diagnosing the disparities as well presenting evidences for the planning in health and strength health care system in achieving equity, welfare and social protection of children.

Supplementary Information

Supplementary information accompanies this paper at 10.1186/s12887-020-02398-x.

Removal of point-of-sale tobacco displays in Bogor city, Indonesia: A spatial analysis

INTRODUCTION

Indonesia contributes over 61 million smokers to global tobacco users, and the smoking prevalence is increasing among young people. In October 2017, Bogor city started the ban on tobacco displays at point-of-sale (POS), starting with modern cigarette retailers. This study aims to assess compliance with the ban and the visibility of POS with tobacco displays around educational facilities.

METHODS

We included 266 modern retailers surveyed throughout the city during November and December 2017. Compliance indicators included no tobacco product displays, advertisements, promotions, and sponsorship. We conducted spatial and quantitative analyses in ArcMap 10.6 and Stata 15.1, respectively.

RESULTS

Immediately following the ban, the compliance with all four criteria was high (83%). However, POS in areas with higher population density and poverty rates had significantly lower compliance. We also found that the ban reduced the visibility of tobacco displays around schools and universities.

CONCLUSIONS

Compliance with the ban was high, which helped to reduce the visibility of tobacco displays around educational facilities.

Identifying Infectious Diarrhea Hot spots and Associated Socioeconomic Factors in Anhui Province, China

Infectious diarrhea cases have increased during the past years in the Anhui Province of China, but little is known about its spatial cluster pattern and associated socioeconomic factors. We obtained county-level total cases of infectious diarrhea in 105 counties of Anhui in 2016 and computed age-adjusted rates. Socioeconomic factors were collected from the Statistical Yearbook. Hot spot analysis was used to identify hot and cold spot counties for infectious diarrhea incidence. We then applied binary logistic regression models to determine the association between socioeconomic factors and hot spot or cold spot clustering risk. Hot spot analysis indicated there were both significant hot spot (29 counties) and cold spot (18 counties) clustering areas for infectious diarrhea in Anhui (P < 0.10). Multivariate binary logistic regression results showed that infectious diarrhea hot spots were positively associated with per capita gross domestic product (GDP), with an adjusted odds ratio (AOR): 3.51, 95% CI: 2.09-5.91, whereas cold spots clustering were positively associated with the number of medical staffs (AOR: 1.18, 95% CI: 1.08-1.29) and negatively associated with the number of public health physicians (AOR: 0.27, 95% CI: 0.09-0.86). We identified locations for hot and cold spot clusters of infectious diarrhea incidence in Anhui, and the clustering risks were significantly associated with health workforce resources and the regional economic development. Targeted interventions should be carried out with considerations of regional socioeconomic conditions.

Leprosy in urban space, areas of risk for disability and worsening of this health condition in Foz Do Iguaçu, the border region between Brazil, Paraguay and Argentina

BACKGROUND

Leprosy is a public health problem and a challenge for endemic countries, especially in their border regions where there are intense migration flows. The study aimed to analyse the dynamics of leprosy, in order to identify areas of risk for the occurrence of the disease and disability and places where this health condition is worsening.

METHOD

This ecological study considered the new cases of leprosy reported in the municipality of Foz do Iguaçu from 2003 to 2015. Spatial and spatial-temporal scan statistics were used to identify the risk areas for the occurrence of leprosy, as well as the Getis-Ord Gi and Getis-Ord Gi* methods. Areas of risk for disabilities were identified by the scan statistic and kernel density estimation.

RESULTS

A total of 840 cases were reported, of which 179 (21.3%) presented Grade 1 or 2 disabilities at the time of diagnosis. Leprosy risk areas were concentrated in the Southern, Eastern and Northeastern Health Districts of the municipality. The cases of Grade 2 disability were observed with higher intensity in regions characterized by high population density and poverty.

CONCLUSION

The results of the study have revealed changes in the pattern of areas at risk of leprosy according to the investigated periods. In addition, it was possible to verify disabilities as a condition present in the investigated cases, or that may be related to the late diagnosis of the disease. In the areas of risk identified, patients have reported worse physical disability after diagnostic confirmation, or indicate inadequate clinical examination, reinforcing the need for structuring leprosy control services in a qualified manner.

Visibility and hotspots of outdoor tobacco advertisement around educational facilities without an advertising ban: Geospatial analysis in Surabaya City, Indonesia

INTRODUCTION

Despite having over 60 million smokers in 2018, Indonesia still lacks tobacco control measures, including an outdoor tobacco advertising ban. This study aimed to provide evidence on the visibility and hotspots of advertisements around educational facilities in a city without a ban.

METHODS

We collected data on the locations of outdoor tobacco advertisements and schools and universities in Surabaya city. We conducted buffer and hotspots analyses using ArcMap. Using Getis-Ord Gi* statistics, hotspot analysis identifies significant clusters with a high number of advertisements.

RESULTS

We found 307 large and medium-sized outdoor tobacco advertisements and 1287 educational facilities (1199 schools, 88 universities). Almost 80% of those advertisements (237 units) were just 300 m away (10-minute walk) from primary schools and high schools in the city. More than half of all schools (652) and two-thirds of all universities (59) were inside hotspots where there were statistically significant clusters with a high number of advertisements. These hotspots were more densely populated and more-deprived areas.

CONCLUSIONS

There was high visibility of large and medium-sized outdoor tobacco advertisements around educational facilities in the city without the ban.

Geospatial epidemiology of hepatitis C infection in Egypt 2017 by governorate

BACKGROUND

Geographic Information Systems (GIS) and spatial epidemiological methods may provide a basis for disease investigation through which hotspots and disease determinants can be identified. Applying these methods for hepatitis C virus (HCV) in Egypt would support a more effective strategy to control its transmission. Therefore, this study used GIS software to draw one of the first HCV maps in Egypt elucidating and analyzing geographical and epidemiological differences in HCV distribution within the country.

METHODS

A cross-sectional survey of 21 governorates (n = 12169, 8080 rural, 3733 urban and 356 slums areas) was completed. All participants were interviewed regarding potential exposures to HCV. Third generation ELISA was used to test serum for HCV antibody. Quantitative real-time RT-PCR was used to test anti-HCV positive subjects for HCV-RNA.

RESULTS

The participants ranged in age from 14-90 years. Overall, anti-HCV sero-prevalence was 14.8%. The prevalence of HCV-RNA, was 9.5%. Proportionally, 65.8% of anti-HCV positives were positive for HCV-RNA. The map of Egyptian governorates highlighted the darkest spot of HCV infection in Menoufeya (37.8%) followed by Beni Suef (29.2%) and Minya (28.6%). Anti-HCV prevalence was higher among males and logistic regression models revealed a strong independent association with increasing age, rural residence and parenteral anti-schistosomal therapy.

CONCLUSIONS

Rural residences and HCV hotspots should be prioritized for HCV prevention programs. The unique age distribution first shown in this study shows that the older age groups (≥60 years old) constitutes a considerable reservoir of infection and must not be neglected.

Detection of risk clusters for deaths due to tuberculosis specifically in areas of southern Brazil where the disease was supposedly a non-problem

Background

Tuberculosis (TB) is the infectious disease that kills the most people worldwide. The use of geoepidemiological techniques to demonstrate the dynamics of the disease in vulnerable communities is essential for its control. Thus, this study aimed to identify risk clusters for TB deaths and their variation over time.

Methods

This ecological study considered cases of TB deaths in residents of Londrina, Brazil between 2008 and 2015. We used standard, isotonic scan statistics for the detection of spatial risk clusters. The Poisson discrete model was adopted with the high and low rates option used for 10, 30 and 50% of the population at risk, with circular format windows and 999 replications considered the maximum cluster size. Getis-Ord Gi* (Gi*) statistics were used to diagnose hotspot areas for TB mortality. Kernel density was used to identify whether the clusters changed over time.

Results

For the standard version, spatial risk clusters for 10, 30 and 50% of the exposed population were 4.9 (95% CI 2.6–9.4), 3.2 (95% CI: 2.1–5.7) and 3.2 (95% CI: 2.1–5.7), respectively. For the isotonic spatial statistics, the risk clusters for 10, 30 and 50% of the exposed population were 2.8 (95% CI: 1.5–5.1), 2.7 (95% CI: 1.6–4.4), 2.2 (95% CI: 1.4–3.9), respectively. All risk clusters were located in the eastern and northern regions of the municipality. Additionally, through Gi*, hotspot areas were identified in the eastern and western regions.

Conclusions

There were important risk areas for tuberculosis mortality in the eastern and northern regions of the municipality. Risk clusters for tuberculosis deaths were observed in areas where TB mortality was supposedly a non-problem. The isotonic and Gi* statistics were more sensitive for the detection of clusters in areas with a low number of cases; however, their applicability in public health is still restricted.

The distribution and socioeconomic burden of Hepatitis C virus in South Australia: a cross-sectional study 2010-2016

BACKGROUND

Hepatitis C virus infection (HCV) is a communicable disease of increasing global importance with 1.75 million new infections and 400,000 related deaths annually. Until recently, treatment options have had low uptake and most infected people remain untreated. New Direct Acting Antiviral medications can clear the virus in around 95% of cases, with few side-effects. These medications are restricted in most countries but freely accessible in Australia, yet most people still remain untreated. This study applies a cross-sectional research design to investigate the socio-spatial distribution of HCV in South Australia, to identify vulnerable populations, and examine epidemiological factors to potentially inform future targeted strategies for improved treatment uptake.

METHOD

HCV surveillance data were sourced from South Australia's Communicable Diseases Control Branch and socio-economic population data from the Australian Bureau of Statistics from January 2010 to December 2016 inclusive. HCV cases were spatially mapped at postcode level. Multivariate logistic regression identified independent predictors of demographic risks for HCV notification and notification source.

RESULTS

HCV notifications (n = 3356) were seven times more likely to be from people residing in the poorest areas with high rates of non-employment (75%; n = 1876) and injecting drug use (74%; n = 1862) reported. Notifications among Aboriginal and Torres Strait Islander people were around six times that of non-Indigenous people. HCV notifications negatively correlated (Spearman's rho - 0.426; p < 0.001) with socio-economic status (residential postcode socio-economic resources Index). History of imprisonment independently predicted HCV diagnoses in lesser economically-resourced areas (RR1.5; p < 0.001). Independent predictors of diagnosis elsewhere than in general practices were non-employment (RR 4.6; p = 0.028), being male (RR 2.5; p < 0.001), and younger than mean age at diagnosis (RR 2.1; p = 0.006).

CONCLUSIONS

Most people diagnosed with HCV were from marginalised sub-populations. Given general practitioners are pivotal to providing effective HCV treatment for many people in Australia a most concerning finding was that non-employed people were statistically less likely to be diagnosed by general practitioners. These findings highlight a need for further action aimed at improving healthcare access and treatment uptake to help reduce the burden of HCV for marginalised people, and progress the vision of eliminating HCV as a major public health threat.

Detecting spatio-temporal hotspots of scarlet fever in Taiwan with spatio-temporal Gi* statistic

A resurgence of scarlet fever has caused many pediatric infections in East Asia and the United Kingdom. Although scarlet fever in Taiwan has not been a notifiable infectious disease since 2007, the comprehensive national health insurance data can still track its trend. Here, we used data from the open data portal of the Taiwan Centers for Disease Control. The scarlet fever trend was measured by outpatient and hospitalization rates from 2009 to 2017. In order to elucidate the spatio-temporal hotspots, we developed a new method named the spatio-temporal Gi* statistic, and applied Joinpoint regression to compute the annual percentage change (APC). The overall APCs in outpatient and hospitalization were 15.1% (95% CI: 10.3%-20.2%) and 7.7% (95%CI: 4.5% -10.9%). The major two infected groups were children aged 5-9 (outpatient: 0.138 scarlet fever diagnoses per 1,000 visits; inpatient: 2.579 per 1,000 visits) and aged 3-4 (outpatient: 0.084 per 1,000 visits; inpatient: 1.469 per 1,000 visits). We found the counties in eastern Taiwan and offshore counties had the most hotspots in the outpatient setting. In terms of hospitalization, the hotspots mostly occurred in offshore counties close to China. With the help of the spatio-temporal statistic, health workers can set up enhanced laboratory surveillance in those hotspots.

Applying core theory and spatial analysis to identify hepatitis C virus infection "core areas" in British Columbia, Canada

"Core areas" of transmission for bacterial sexually transmitted infections have been identified. However, it is unclear whether core areas apply to viral infections, such as hepatitis C virus (HCV). We used geographic mapping and spatial analysis to identify distinct core areas of HCV infection in British Columbia (BC) using the BC Hepatitis Testers Cohort (BC-HTC), 1990-2013. The BC-HTC includes all BC residents tested for HCV (~1.5 million; 1990-2013). Core HCV infection areas were identified spatially and temporally for five time periods (1990-1993, 1994-1998, 1999-2003, 2004-2008 and 2009-2013) through thematic mapping, Kernel Density Estimation, Hotspot analysis and cluster analysis at the Census dissemination area level in ArcGIS and SatScan. HCV infection core areas were consistently identified. HCV core areas expanded from the downtown of major cities in different regions of BC (Metro Vancouver, Vancouver Island, and Northern BC; 1990-1998), to smaller cities in Metro Vancouver and Interior BC (2000 onwards). Statistically significant clusters, or hotspots, were also observed for downtown Vancouver, Northern BC (Prince George) and Vancouver Island from 1990 to 2008 with expansion to other urban areas in Metro Vancouver from 1990-2013. Statistically significant clusters persisted after adjustment for injection drug use, number of HCV tests, age, sex, material and social deprivation. Persistence of areas with high HCV diagnoses rates in Vancouver and Prince George supports the theory of core areas of HCV transmission. Identification of core areas can inform prevention, care and treatment programme interventions and evaluate their impact over time.

Detecting spatial clusters of HIV and hepatitis coinfections

BACKGROUND

People with HIV infection in the United States are often affected by chronic viral hepatitis. These coinfected people with either HBV or HCV are at increased risk for serious, life-threatening complications. Coinfections with viral hepatitis may also complicate the delivery of anti-retroviral therapy (ART) by escalating the risk of drug-related hepatoxicity. According to the Centers for Disease Control and Prevention (CDC), approximately 10 percent of people with HIV in the United States also have HBV, and 25 percent also have HCV coinfection. With the advent of highly active antiretroviral therapy (HAART) and the increased life-expectancy of HIV patients, clinicians are more likely to be confronted with issues related to co-infection and the management challenges that they present, especially in resource-limited settings. The purpose of this analysis was to identify geographical clusters of HIV- (HBV/HCV) co-infection and compared to the geographical clusters of not co-infected using DC, Department of Health surveillance data. The results of the analysis will be used to target resources to areas at risk.

METHODS

HIV and Hepatitis surveillance data were matched among cases diagnosed between 1980 and 2016. HIV-hepatitis co-infected and the not co-infected spatial clusters were detected using discrete Poisson model. Kulldorff's spatial scan statistic method was implemented in the free software tool called SaTScan which has been widely adopted for detecting disease cluster. The analysis was conducted by tracts, but for visualization, ease of interpretation and assist in policy making the tract map was overlaid with the ward map using ArcGIS 10.5.1.

RESULTS

Between 1980 and 2016, there were 12,965 diagnosed cases of HIV, of which 2,316 HIV/Hepatitis matches were identified. Of the 2316 co-infected people living in DC, 25 percent (N = 590) of people had HBV, and 75 percent (N = 1,726) had HCV. Out of 12,965 diagnosed cases, remaining 10,649 did not have any co-infections (not co-infected). IDU (27.16 percent) and MSM (32.86 percent) were the highest mode of transmission for co-infected population. African-American were reported 83.64 percent (N = 1,937) among co-infection population. Three clusters were identified for both co-infected population in DC. The largest cluster radius for co-infected analysis covers wards 6, 7 and 8 as well as large parts of 2 and 5 (p < 0.001). Multiple clusters were identified for not co-infected population (p < 0.001). IDU (n = 450) was the highest mode of transmission for the co-infected clusters. For all clusters combined of not co-infected population highest mode of transmission were MSM (n = 2,534). This analysis also showed racial disparity, economic deprivation and lack of education were prominent in the co-infected clusters.

CONCLUSION

We identified locations of high risk clusters where enhanced hepatitis and HIV prevention, treatment, and care can help combat the epidemic. The clusters radius expands into the neighboring state of Maryland as well. The findings from this analysis will be used to target area based public health policy and healthcare interventions for HIV-hepatitis. It is recommended based on the analysis that needle exchange programs can successfully control new HIV infections as well as hepatitis co-infections.

Disparities in Access to Direct Acting Antiviral Regimens for Hepatitis C Virus (HCV): The Impact of Race and Insurance Status

Despite highly effective and well-tolerated regimens for treating hepatitis C virus (HCV), patients face barriers in accessing treatment. In addition to suboptimal HCV screening programs and lack of effective linkage-to-care, other barriers include strict requirements from some payers to cover treatment. This study reports insurance status and Hispanic ethnicity as predictors of not receiving treatment. These barriers occur despite the fact that HCV is the most common indication for liver transplantation and cause of hepatocellular carcinoma in the U.S. Therefore, it is critical that policymakers bring all the stakeholders together and develop a national policy to eradicate HCV infection from the U.S.

Under one roof: identification, evaluation, and treatment of chronic hepatitis C in addiction care

For over a decade, the vast majority of new hepatitis C virus (HCV) infections have been among young people who inject drugs (PWID). Well-characterized gaps in chronic HCV diagnosis, evaluation, and treatment have resulted in fewer than 5% of PWID receiving HCV treatment. While interferon-based treatment may have intentionally been foregone during part of this time in anticipation of improved oral therapies, the overall pattern points to deficiencies and treatment exclusions in the health care system. Treatment for HCV with all-oral, highly effective direct-acting antiviral medication for 12 weeks or less is now the standard of care, putting renewed focus on effective delivery of care. We describe here both the need for and process of chronic HCV care under the roof of addiction medicine.