Spatial epidemiology: An empirical framework for syndemics research

Defining Spatial Epidemiology: A Systematic Review and Re-orientation

BACKGROUND

Spatial epidemiology has emerged as an important subfield of epidemiology over the past quarter century. We trace the origins of spatial epidemiology and note that its emergence coincided with technological developments in spatial statistics and geography. We hypothesize that spatial epidemiology makes important contributions to descriptive epidemiology and analytic risk-factor studies but is not yet aligned with epidemiology's current focus on causal inference and intervention.

METHODS

We conducted a systematic review of studies indexed in PubMed that used the term "spatial epidemiolog*" in the title, abstract, or keywords. Excluded articles were not written in English, examined disease in animals, or reported biologic pathogen distribution only. We coded the included papers into five categories (review, demonstration of method, descriptive, analytic, and intervention) and recorded the unit of analysis (i.e., individual vs. ecological). We additionally examined articles coded as analytic ecologic studies using scales for lexical content.

RESULTS

A total of 482 articles met the inclusion criteria, including 76 reviews, 117 demonstrations of methods, 122 descriptive studies, 167 analytic studies, and 0 intervention studies. Demonstration studies were most common from 2006 to 2014, and analytic studies were most common after 2015. Among the analytic ecologic studies, those published in later years used more terms relevant to spatial statistics (incidence rate ratio =1.3; 95% confidence interval [CI] = 1.1, 1.5) and causal inference (incidence rate ratio =1.1; 95% CI = 1.1, 1.2).

CONCLUSIONS

Spatial epidemiology is an important and growing subfield of epidemiology. We suggest a re-orientation to help align its practice with the goals of contemporary epidemiology.

Synergistic Epidemic or Syndemic: An Emerging Pattern of Human Diseases

Synergistic epidemics refer to the phenomenon where the occurrence and interaction of multiple diseases or health conditions exacerbate their individual impact, leading to complex health challenges and increased vulnerability in populations. Syndemics are a complex, multilevel phenomenon. In a population with biological interactions, a syndemic is the accumulation of two or more concurrent or sequential epidemics, which significantly worsens the situation. Disease concentration, disease interaction, and their underlying social forces, such as poverty and social inequality, are the fundamental concepts. Extensive political, economic, and cultural factors have contributed to cluster epidemics of several infectious diseases, particularly HIV and tuberculosis. Concerning the SAVA (substance abuse, violence, AIDS) syndemic, this narrative review article explores the complex interactions between substance abuse, violence, and HIV/AIDS. Further, it describes in-depth interactions between the COVID-19 syndemic's health conditions, societal factors, biological factors, and global dynamics. The review also emphasizes how infectious and non-communicable diseases interact, emphasizing how having one condition can make the severity and outcomes of another worse. It investigates the causes of synergistic epidemics and the impact of environmental factors. Syndemics acknowledge that the presence of one condition can worsen the severity and progression of others and take into account the intricate relationships between diseases. We can create more efficient plans to enhance health outcomes, lessen disparities, and promote healthier communities by understanding the connections between disorders and the underlying social determinants. This narrative review provides insights into the emerging patterns of human diseases within synergistic epidemics.

A review of place-related contextual factors in syndemics research

This review investigates the extent to which a place-based approach has been used to conceptualize context, as well as the place-related contextual factors explored in studies that explicitly invoked a syndemic framework. The literature search focused on 29 peer-reviewed empirical syndemic studies. Only 11 studies used a place-based approach to define and measure contextual factors and the spatial context was denoted using administrative boundaries such as census tracts, counties, and countries. A narrow range of place-related contextual factors were explored and most of them were related to social and economic factors that were used to define a place. Methodological gaps like a paucity of multilevel studies and studies using a place-based approach to measure context were identified. Future syndemics research should leverage multidimensional geospatial approaches to decipher the role of place-related contextual factors in syndemic dynamics.

A Dynamic Spatial Factor Model to Describe the Opioid Syndemic in Ohio

BACKGROUND

The opioid epidemic has been ongoing for over 20 years in the United States. As opioid misuse has shifted increasingly toward injection of illicitly produced opioids, it has been associated with HIV and hepatitis C transmission. These epidemics interact to form the opioid syndemic.

METHODS

We obtain annual county-level counts of opioid overdose deaths, treatment admissions for opioid misuse, and newly diagnosed cases of acute and chronic hepatitis C and newly diagnosed HIV from 2014 to 2019. Aligned with the conceptual framework of syndemics, we develop a dynamic spatial factor model to describe the opioid syndemic for counties in Ohio and estimate the complex synergies between each of the epidemics.

RESULTS

We estimate three latent factors characterizing variation of the syndemic across space and time. The first factor reflects overall burden and is greatest in southern Ohio. The second factor describes harms and is greatest in urban counties. The third factor highlights counties with higher than expected hepatitis C rates and lower than expected HIV rates, which suggests elevated localized risk for future HIV outbreaks.

CONCLUSIONS

Through the estimation of dynamic spatial factors, we are able to estimate the complex dependencies and characterize the synergy across outcomes that underlie the syndemic. The latent factors summarize shared variation across multiple spatial time series and provide new insights into the relationships between the epidemics within the syndemic. Our framework provides a coherent approach for synthesizing complex interactions and estimating underlying sources of variation that can be applied to other syndemics.

Spatial Analysis of the Alcohol, Intimate Partner Violence, and HIV Syndemic Among Women in South Africa

The co-occurrence of and synergistic interactions between substance abuse, violence, and HIV, known as the "SAVA syndemic," is thought to be a driver of women's elevated risk for HIV in sub-Saharan Africa. This study uses data from the 2016 South African Demographic and Health Survey (DHS) and the 2016 South African Census to examine geospatial associations between alcohol use, intimate partner violence (IPV), unprotected sex, and HIV status among a population-based sample of 8528 South African women (age 15-49). Results support the geographic clustering of alcohol use, unprotected sex, and IPV, but not HIV, and geospatial clustering of HIV alone. This study highlights the need for geographically-tailored interventions to address syndemics through integrated interventions, such as those simultaneously focused on alcohol, IPV, and sexual risk reduction, and points to the need for more targeted research to link these factors to HIV from a place-based risk perspective.

The Rise of Gastrointestinal Cancers as a Global Phenomenon: Unhealthy Behavior or Progress?

The overall burden of cancer is rapidly increasing worldwide, reflecting not only population growth and aging, but also the prevalence and spread of risk factors. Gastrointestinal (GI) cancers, including stomach, liver, esophageal, pancreatic, and colorectal cancers, represent more than a quarter of all cancers. While smoking and alcohol use are the risk factors most commonly associated with cancer development, a growing consensus also includes dietary habits as relevant risk factors for GI cancers. Current evidence suggests that socioeconomic development results in several lifestyle modifications, including shifts in dietary habits from local traditional diets to less-healthy Western diets. Moreover, recent data indicate that increased production and consumption of processed foods underlies the current pandemics of obesity and related metabolic disorders, which are directly or indirectly associated with the emergence of various chronic noncommunicable conditions and GI cancers. However, environmental changes are not restricted to dietary patterns, and unhealthy behavioral features should be analyzed with a holistic view of lifestyle. In this review, we discussed the epidemiological aspects, gut dysbiosis, and cellular and molecular characteristics of GI cancers and explored the impact of unhealthy behaviors, diet, and physical activity on developing GI cancers in the context of progressive societal changes.

Applying the syndemic framework to cancer research for effective cancer control in low- and middle-income countries

Cancer burden is increasing rapidly globally, especially in low- and middle-income countries (LMICs), which already face a double burden of infectious diseases and other non-communicable diseases (NCDs). LMICs also struggle with poor social determinants of health, leading to cancer health disparities, such as delayed diagnoses and increased death rates due to cancer. Contextually, relevant research needs to be prioritised in these regions to ensure feasible, evidence-based healthcare planning and delivery for cancer prevention and control. A syndemic framework has been used to study the disease clustering of infectious diseases and NCDs across varied social contexts to understand how diseases interact adversely and how the wider environmental context and other socioeconomic factors contribute to poor health outcomes within specific populations. We propose using this model to study the 'syndemic of cancers' in the disadvantaged population of LMICs and suggest ways for the clear operationalisation of the syndemic framework through multidisciplinary evidence-generation models for the delivery of integrated, socially conscious interventions for effective cancer control.

L’approche syndémique appliquée à la santé des minorités sexuelles et de genre : étude de la portée

INTRODUCTION

Sexual and gender minorities (SGM) represent a vulnerable population, disproportionately affected by mental health issues, a higher exposure to violence and a higher prevalence of sexually transmitted infections, including HIV, for some subgroups. Derived from medical anthropology, the concept of a syndemic consists in the clustering and interaction between multiple health conditions through adverse social conditions such as discrimination or precarity. Confronted to the multitude of adverse conditions affecting SGM, this framework is pertinent to study their health and to propose interventions.

PURPOSE OF RESEARCH

The purpose of this scoping review is to synthetize the knowledge regarding syndemic theory applied to sexual and gender minorities in order to propose concrete suggestions for scholarly research and field intervention.

RESULTS

126 papers were included. European data as well as data concerning sexual minority women and transgender men are scarce. A co-occurrence of psychosocial conditions fostered by stigmatization is well-established. Furthermore, the presence of a syndemic was associated to sexual higher odds of acquiring HIV, suicidal behavior and healthcare utilization.

CONCLUSIONS

The syndemic framework is important to the health of SGM, both for academic and interventional purposes. Current priorities should be to act against structural disadvantages leading to a syndemic, to improve our knowledge on SGM health in European context and to develop local programs based on peer-support.

Progress on application of spatial epidemiology in ophthalmology

Most ocular diseases observed with cataract, chlamydia trachomatis, diabetic retinopathy, and uveitis, have their associations with environmental exposures, lifestyle, and habits, making their distribution has certain temporal and spatial features based essentially on epidemiology. Spatial epidemiology focuses on the use of geographic information systems (GIS), global navigation satellite systems (GNSS), and spatial analysis to map spatial distribution as well as change the tendency of diseases and investigate the health services status of populations. Recently, the spatial epidemic approach has been applied in the field of ophthalmology, which provides many valuable key messages on ocular disease prevention and control. This work briefly reviewed the context of spatial epidemiology and summarized its progress in the analysis of spatiotemporal distribution, non-monitoring area data estimation, influencing factors of ocular diseases, and allocation and utilization of eye health resources, to provide references for its application in the prevention and control of ocular diseases in the future.

Utilizing Baidu Index to Investigate Seasonality, Spatial Distribution and Public Attention of Dry Eye Diseases in Chinese Mainland

Purpose

To explore the characteristics of spatial-temporal prevalence and public attention of dry eye diseases (DED) through Baidu Index (BI) based on infodemiology method.

Methods

The data about BI of DED were collected from Baidu search engine using "Dry eye diseases" as keyword. The spatial and temporal distribution of DED were analyzed through timeseries data decomposition as well as spatial autocorrelation and hotspot detection of BI about DED. The most popular related words and demographic characteristics were recorded to determine the public attention of DED.

Results

The trends of BI about DED in Chinese mainland had gradually increased over time with a rapid increase from 2012 to 2014 and in 2018. The results of timeseries decomposition indicated that there was seasonality in the distribution of BI about DED with the peak in winter, especially in northern regions. The geographic distribution demonstrated the search activities of DED was highest in the east of Chinese mainland while lowest in the west. The vast majority of people searching for DED were teenagers (20-29 years), with a predominance of females. Glaucoma, keratitis and conjunctivitis were the diseases most often confused with DED, and the artificial tears were the most common treatment for DED in Chinese mainland according to the BI about DED.

Conclusions

The analysis revealed the seasonality, geographic hotspots and public concern of DED through BI in Chinese mainland, which provided new insights into the epidemiology of DED.

Spatio-temporal modeling of COVID-19 prevalence and mortality using artificial neural network algorithms

The outbreak of coronavirus disease (COVID-19) has become one of the most challenging global concerns in recent years. Due to inadequate worldwide studies on spatio-temporal modeling of COVID-19, this research aims to examine the relative significance of potential explanatory variables (n = 75) concerning COVID-19 prevalence and mortality using multilayer perceptron artificial neural network topology. We utilized ten variable importance analysis methods to identify the relative importance of the explanatory variables. The main findings indicated that several variables were persistently among the most influential variables in all periods. Regarding COVID-19 prevalence, unemployment and population density were among the most influential variables with the highest importance scores. While for COVID-19 mortality, health-related variables such as diabetes prevalence and number of hospital beds were among the most significant variables. The obtained findings from this study might provide general insights for public health policymakers to monitor the spread of disease and support decision-making.

Are There Global Syndemics?

In this article, we address the nature of syndemics and whether, as some have asserted, these epidemiological phenomena are global configurations. Our argument that syndemics are not global rests on recognition that they are composed of social/environment contexts, disease clusters, demographics, and biologies that vary across locations. These points are illustrated with the cases of syndemics involving COVID-19, diabetes mellitus, and HIV/AIDS. We draw on theoretical discourse from epidemiology, biology, and anthropology to present what we believe is a more accurate framework for thinking about syndemics with shared elements.

The SARS-CoV-2 pandemic: A syndemic perspective

The SARS-CoV-2 pandemic has affected communities, populations, and countries throughout the world. As the SARS-CoV-2 pandemic developed, the extent to which the disease interacted with already existing endemic, non-communicable and infectious diseases became evident, hence deeply influencing health outcomes. Additionally, a synergistic effect has been demonstrated also with socio-economic, cultural, and contextual determinants of health which seem to contribute to poorer health and accumulating social disadvantages. In this essay, using as a starting point the syndemic theory that translates the cumulative and intertwined factors between different epidemics, we argue that the SARS-CoV-2 is a one health issue of a syndemic nature and that the failure to acknowledge this contributes to weakened policy-making processes and public health responses and ineffective health policies and programs.