Quantifying Poverty as a Driver of Ebola Transmission

Ebola, informal settlements, and the role of place in infectious disease vulnerability: evidence from the 2014-16 outbreak in urban Sierra Leone

Studies of vulnerability often focus on the differential susceptibility of marginalised groups to the effects of disaster. This paper considers how vulnerability is also associated with the characteristics of place, especially the social setting of the informal settlement. In this light, it assesses specifically how cultural, historical, and political economic forces resulted in increased vulnerability to Ebola virus disease (EVD) within informal settlements in Sierra Leone during the epidemic of 2014-16. Key informant and community member interviews and focus-group discussions in two communities revealed that increased vulnerability to EVD could, at least in part, be attributed to a set of place-based social factors pertaining to 'community beliefs and practices' (importance of family ties, funeral rites, traditional healing) and 'structural poverty and low socioeconomic status' (poor healthcare provision, mobility patterns, overcrowding). Together, these different factors demonstrate how multiple and intersecting vulnerabilities contribute to the spatial production of disease risk.

Geographical variations and district-level factors associated with COVID-19 mortality in Indonesia: a nationwide ecological study

BACKGROUND

Ensuring health equity, especially for vulnerable populations in less developed settings with poor health system is essential for the current and future global health threats. This study examined geographical variations of COVID-19 mortality and its association with population health characteristics, health care capacity in responding pandemic, and socio-economic characteristics across 514 districts in Indonesia.

METHODS

This nationwide ecological study included aggregated data of COVID-19 cases and deaths from all 514 districts in Indonesia, recorded in the National COVID-19 Task Force database, during the first two years of the epidemic, from 1 March 2020 to 27 February 2022. The dependent variable was district-level COVID-19 mortality rate per 100,000 populations. The independent variables include district-level COVID-19 incidence rate, population health, health care capacity, and socio-demographics data from government official sources. We used multivariable ordinal logistic regression to examine factors associated with higher mortality rate.

RESULTS

Of total 5,539,333 reported COVID-19 cases, 148,034 (2.7%) died, and 5,391,299 (97.4%) were recovered. The district-level mortality rate ranged from 0 to 284 deaths per 100,000 populations. The top five districts with the highest mortality rate were Balikpapan (284 deaths per 100,000 populations), Semarang (263), Madiun (254), Magelang (250), and Yogyakarta (247). A higher COVID-19 incidence (coefficient 1.64, 95% CI 1.22 to 1.75), a higher proportion of ≥ 60 years old population (coefficient 0.26, 95% CI 0.06 to 0.46), a higher prevalence of diabetes mellitus (coefficient 0.60, 95% CI 0.37 to 0.84), a lower prevalence of obesity (coefficient -0.32, 95% CI -0.56 to -0.08), a lower number of nurses per population (coefficient -0.27, 95% CI -0.50 to -0.04), a higher number of midwives per population (coefficient 0.32, 95% CI 0.13 to 0.50), and a higher expenditure (coefficient 0.34, 95% CI 0.10 to 0.57) was associated with a higher COVID-19 mortality rate.

CONCLUSION

COVID-19 mortality rate in Indonesia was highly heterogeneous and associated with higher COVID-19 incidence, different prevalence of pre-existing comorbidity, healthcare capacity in responding the pandemic, and socio-economic characteristics. This study revealed the need of controlling both COVID-19 and those known comorbidities, health capacity strengthening, and better resource allocation to ensure optimal health outcomes for vulnerable population.

Association between Conflict and Cholera in Nigeria and the Democratic Republic of the Congo

Cholera outbreaks contribute substantially to illness and death in low- and middle-income countries. Cholera outbreaks are associated with several social and environmental risk factors, and extreme conditions can act as catalysts. A social extreme known to be associated with infectious disease outbreaks is conflict, causing disruption to services, loss of income, and displacement. To determine the extent of this association, we used the self-controlled case-series method and found that conflict increased the risk for cholera in Nigeria by 3.6 times and in the Democratic Republic of the Congo by 2.6 times. We also found that 19.7% of cholera outbreaks in Nigeria and 12.3% of outbreaks in the Democratic Republic of the Congo were attributable to conflict. Our results highlight the value of providing rapid and sufficient assistance during conflict-associated cholera outbreaks and working toward conflict resolution and addressing preexisting vulnerabilities, such as poverty and access to healthcare.

The Slums in the Mirror of Health: A Systematic Review Analysis from Iran

Background

One billion worldwide population is living in slum areas that mostly accompanied with high rates of poverty, illiteracy, unemployment, unhealthy situation, and inappropriate health-care services. The prediction of enormous growth of slums by 2030 led to a raise to address the "plight of slums" in Sustainable Development Goals (SDGs).

Methods

To address evidence-based health-related priorities, we conducted a systematic review to summarizing evidences on health situations of slums population in Iran. Six electronic databases were systematically searched for published studies without any restriction on age, sex, and language to assess health situations of slums in Iran reported by following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol. All identified articles were screened, quality assessed, and data extracted by two authors independently.

Results

The finding of this systematic review in addition to overall view categorized in five categories: health system, reproductive health, infectious diseases, noncommunicable diseases and their risk factors, social issues besides overall situation of Slums.

Conclusions

Community-based participatory interventions with socioeconomic approach on modifiable risk factors; active response of health system; establishment new health care centers in slum areas; augmenting the quality of care; active case finding; and elevating health knowledge, attitude, and practice is crucial to achieve SDG's in Slum area.

COVID-19 mortality and deprivation: pandemic, syndemic, and endemic health inequalities

COVID-19 has exacerbated endemic health inequalities resulting in a syndemic pandemic of higher mortality and morbidity rates among the most socially disadvantaged. We did a scoping review to identify and synthesise published evidence on geographical inequalities in COVID-19 mortality rates globally. We included peer-reviewed studies, from any country, written in English that showed any area-level (eg, neighbourhood, town, city, municipality, or region) inequalities in mortality by socioeconomic deprivation (ie, measured via indices of multiple deprivation: the percentage of people living in poverty or proxy factors including the Gini coefficient, employment rates, or housing tenure). 95 papers from five WHO global regions were included in the final synthesis. A large majority of the studies (n=86) found that COVID-19 mortality rates were higher in areas of socioeconomic disadvantage than in affluent areas. The subsequent discussion reflects on how the unequal nature of the pandemic has resulted from a syndemic of COVID-19 and endemic inequalities in chronic disease burden.

Estimation of Ebola’s spillover infection exposure in Sierra Leone based on sociodemographic and economic factors

Zoonotic diseases spread through pathogens-infected animal carriers. In the case of Ebola Virus Disease (EVD), evidence supports that the main carriers are fruit bats and non-human primates. Further, EVD spread is a multi-factorial problem that depends on sociodemographic and economic (SDE) factors. Here we inquire into this phenomenon and aim at determining, quantitatively, the Ebola spillover infection exposure map and try to link it to SDE factors. To that end, we designed and conducted a survey in Sierra Leone and implement a pipeline to analyze data using regression and machine learning techniques. Our methodology is able (1) to identify the features that are best predictors of an individual’s tendency to partake in behaviors that can expose them to Ebola infection, (2) to develop a predictive model about the spillover risk statistics that can be calibrated for different regions and future times, and (3) to compute a spillover exposure map for Sierra Leone. Our results and conclusions are relevant to identify the regions in Sierra Leone at risk of EVD spillover and, consequently, to design and implement policies for an effective deployment of resources (e.g., drug supplies) and other preventative measures (e.g., educational campaigns).

Drivers of African Filovirus (Ebola and Marburg) Outbreaks

Outbreaks of African filoviruses often have high mortality, including more than 11,000 deaths among 28,562 cases during the West Africa Ebola outbreak of 2014-2016. Numerous studies have investigated the factors that contributed to individual filovirus outbreaks, but there has been little quantitative synthesis of this work. In addition, the ways in which the typical causes of filovirus outbreaks differ from other zoonoses remain poorly described. In this study, we quantify factors associated with 45 outbreaks of African filoviruses (ebolaviruses and Marburg virus) using a rubric of 48 candidate causal drivers. For filovirus outbreaks, we reviewed >700 peer-reviewed and gray literature sources and developed a list of the factors reported to contribute to each outbreak (i.e., a "driver profile" for each outbreak). We compare and contrast the profiles of filovirus outbreaks to 200 background outbreaks, randomly selected from a global database of 4463 outbreaks of bacterial and viral zoonotic diseases. We also test whether the quantitative patterns that we observed were robust to the influences of six covariates, country-level factors such as gross domestic product, population density, and latitude that have been shown to bias global outbreak data. We find that, regardless of whether covariates are included or excluded from models, the driver profile of filovirus outbreaks differs from that of background outbreaks. Socioeconomic factors such as trade and travel, wild game consumption, failures of medical procedures, and deficiencies in human health infrastructure were more frequently reported in filovirus outbreaks than in the comparison group. Based on our results, we also present a review of drivers reported in at least 10% of filovirus outbreaks, with examples of each provided.

The prevalence of Post-Ebola Syndrome hearing loss, Sierra Leone

BACKGROUND

Globally, hearing loss is the second leading cause of disability, affecting approximately 18.7% of the world's population. However, the burden of hearing loss is unequally distributed, with the majority of affected individuals located in Asia or Sub-Saharan Africa. Following the 2014 West African Ebola Outbreak, disease survivors began to describe hearing loss as part of the constellation of symptoms known as Post-Ebola Syndrome. The goal of this study was to more fully characterize hearing loss among Ebola Virus Disease (EVD) survivors.

METHODOLOGY AND PRINCIPAL FINDINGS

EVD survivors and their household contacts were recruited (n = 1,12) from Eastern Sierra Leone. Each individual completed a symptom questionnaire, physical exam, and a two-step audiometry process measuring both air and bone conduction thresholds. In comparison to contacts, EVD survivors were more likely to have complaints or abnormal findings affecting every organ system. A significantly greater percentage of EVD survivors were found to have hearing loss in comparison to contacts (23% vs. 9%, p < 0.001). Additionally, survivors were more likely to have bilateral hearing loss of a mixed etiology. Logistic regression revealed that the presence of any symptoms of middle or inner ear (p < 0.001), eye (p = 0.005), psychiatric (p = 0.019), and nervous system (p = 0.037) increased the odds of developing hearing loss.

CONCLUSIONS AND SIGNIFICANCE

This study is the first to use an objective and standardized measurement to report hearing loss among EVD survivors in a clinically meaningful manner. In this study it was found that greater than 1/5th of EVD survivors develop hearing loss. The association between hearing impairment and symptoms affecting the eye and nervous system may indicate a similar mechanism of pathogenesis, which should be investigated further. Due to the quality of life and socioeconomic detriments associated with untreated hearing loss, a greater emphasis must be placed on understanding and mitigating hearing loss following survival to aid in economic recovery following infectious disease epidemics.

Geospatial clustering and correlates of deaths during the Ebola outbreak in Liberia: a Bayesian geoadditive semiparametric analysis of nationally representative cross-sectional survey data

OBJECTIVE

To investigate the extent of geospatial clustering of reported deaths during the Ebola outbreak in Liberia and the covariates associated with the observed clustering.

DESIGN

Cross-sectional study.

PARTICIPANTS

Male and female respondents from the 2019-2020 Liberia Demographic and Health Survey. The analysis covered 11 928 (women=7854 and men=4074) respondents for whom complete data were available.

OUTCOME MEASURES

The outcome variable was the death of a household member or relative during the Ebola outbreak in Liberia, coded 1 if the respondent reported death and 0 otherwise.

METHODS

We applied the Bayesian geoadditive semiparametric regression to examine the extent of geospatial clustering of deaths at the district-level and community-level development and socioeconomic factors associated with the observed clustering.

RESULTS

Almost a quarter (24.8%) of all respondents reported the death of a household member or relative during the Ebola outbreak. The results show that deaths were clustered within districts in six (Grand Cape Mount, Bomi, Monsterrado, Margibi, Gbarpolu and Lofa) of the 15 counties in Liberia. Districts with high death clustering were all near or shared borders with Sierra Leone and Guinea. The community-level development indicators (global human footprint, gross cell production and population density) had a non-linear associative effect with the observed spatial clustering. Also, respondents' characteristics (respondent's age (non-linear effect), educational attainment and urban-rural place of residence) were associated with the observed clustering. The results show that death clustering during outbreaks was constrained to poor settings and impacts areas of moderate and high socioeconomic development.

CONCLUSION

Reported deaths during the Ebola outbreak in Liberia were not randomly distributed at the district level but clustered. The findings highlight the need to identify at-risk populations during epidemics and respond with the needed interventions to save lives.

Pandemic inequity in a megacity: a multilevel analysis of individual, community and healthcare vulnerability risks for COVID-19 mortality in Jakarta, Indonesia

INTRODUCTION

Worldwide, the 33 recognised megacities comprise approximately 7% of the global population, yet account for 20% COVID-19 deaths. The specific inequities and other factors within megacities that affect vulnerability to COVID-19 mortality remain poorly defined. We assessed individual, community-level and healthcare factors associated with COVID-19-related mortality in a megacity of Jakarta, Indonesia, during two epidemic waves spanning 2 March 2020 to 31 August 2021.

METHODS

This retrospective cohort included residents of Jakarta, Indonesia, with PCR-confirmed COVID-19. We extracted demographic, clinical, outcome (recovered or died), vaccine coverage data and disease prevalence from Jakarta Health Office surveillance records, and collected subdistrict level sociodemographics data from various official sources. We used multilevel logistic regression to examine individual, community and subdistrict-level healthcare factors and their associations with COVID-19 mortality.

RESULTS

Of 705 503 cases with a definitive outcome by 31 August 2021, 694 706 (98.5%) recovered and 10 797 (1.5%) died. The median age was 36 years (IQR 24-50), 13.2% (93 459) were <18 years and 51.6% were female. The subdistrict level accounted for 1.5% of variance in mortality (p<0.0001). Mortality ranged from 0.9 to 1.8% by subdistrict. Individual-level factors associated with death were older age, male sex, comorbidities and age <5 years during the first wave (adjusted OR (aOR)) 1.56, 95% CI 1.04 to 2.35; reference: age 20-29 years). Community-level factors associated with death were poverty (aOR for the poorer quarter 1.35, 95% CI 1.17 to 1.55; reference: wealthiest quarter) and high population density (aOR for the highest density 1.34, 95% CI 1.14 to 2.58; reference: the lowest). Healthcare factor associated with death was low vaccine coverage (aOR for the lowest coverage 1.25, 95% CI 1.13 to 1.38; reference: the highest).

CONCLUSION

In addition to individual risk factors, living in areas with high poverty and density, and low healthcare performance further increase the vulnerability of communities to COVID-19-associated death in urban low-resource settings.

Contextualizing mobility during the Ebola epidemic in Liberia

Based on findings from focus groups and key informant interviews conducted at five sites in Liberia between 2018 and 2019, we explore some of the key factors that influenced people's motivation to travel during the 2014-2016 Ebola Virus Disease (EVD). We discuss how these factors led to certain mobility patterns and the implications these had for EVD response. The reasons for individual mobility during the epidemic were multiple and diverse. Some movements were related to relocation efforts as people attempted to extricate themselves from stigmatizing situations. Others were motivated by fear, convinced that other communities would be safer, particularly if extended family members resided there. Individuals also felt compelled to travel during the epidemic to meet other needs and obligations, such as attending burial rites. Some expressed concerns about obtaining food and earning a livelihood. Notably, these latter concerns served as an impetus to travel surreptitiously to evade quarantine directives aimed specifically at restricting mobility. Improvements in future infectious disease response could be made by incorporating contextually-based mobility factors, for example: the personalization of public health messaging through the recruitment of family members and trusted local leaders, to convey information that would help allay fear and combat stigmatization; activating existing traditional community surveillance systems in which entry into the community must first be approved by the community chief; and increased involvement of local leaders and community members in the provision of food and care to those quarantined so that the need to travel for these reasons is removed.

Accuracy and Timeliness of Knowledge Dissemination on COVID-19 Among People in Rural and Remote Regions of China at the Early Stage of Outbreak

Coronavirus disease 2019 (COVID-19) spread throughout China in January 2020. To contain the virus outbreak, the Chinese government took extraordinary measures in terms of public policy, wherein accurate and timely dissemination of information plays a crucial role. Despite all of the efforts toward studying this health emergency, little is known about the effectiveness of public policies that support health communication during such a crisis to disseminate knowledge for self-protection. Particularly, we focus on the accuracy and timeliness of knowledge dissemination on COVID-19 among people in remote regions—a topic largely omitted in existing research. In February 2020, at the early-stages of the COVID-19 outbreak, a questionnaire survey was carried out. In total, 8,520 participants from seven less economically developed provinces situated in the borderlands of China with large ethnic minority groups responded. We analyzed the data through poisson regression and logistic regression analyses. We found that (1) people in remote regions of China obtained accurate information on COVID-19. Further, they were able to take appropriate measures to protect themselves. (2) Result from both descriptive analysis and multivariable regression analysis revealed that there is no large difference in the accuracy of information among groups. (3) Older, less educated, and rural respondents received information with a significant delay, whereas highly educated, younger, urban residents and those who obtained information through online media were more likely to have received the news of the outbreak sooner and to be up to date on the information. This research provides evidence that disadvantage people in remote regions obtained accurate and essential information required to act in an appropriate manner in responses to the COVID-19 outbreak. However, they obtained knowledge on COVID-19 at a slower pace than other people; thus, further improvement in the timely dissemination of information among disadvantage people in remote regions is warranted.

Pandemic inequalities: emerging infectious diseases and health equity

The frequency and scale of Emerging Infectious Diseases (EIDs) with pandemic potential has been increasing over the last two decades and, as COVID-19 has shown, such zoonotic spill-over events are an increasing threat to public health globally. There has been considerable research into EIDs - especially in the case of COVID-19. However, most of this has focused on disease emergence, symptom identification, chains of transmission, case prevalence and mortality as well as prevention and treatment. Much less attention has been paid to health equity concerns and the relationship between socio-economic inequalities and the spread, scale and resolution of EID pandemics. This commentary article therefore explores socio-economic inequalities in the nature of EID pandemics. Drawing on three diverse case studies (Zika, Ebola, COVID-19), it hypothesises the four main pathways linking inequality and infectious disease (unequal exposure, unequal transmission, unequal susceptibility, unequal treatment) - setting out a new model for understanding EIDs and health inequalities. It concludes by considering the research directions and policy actions needed to reduce inequalities in future EID outbreaks.

Coordinated support for local action: Modeling strategies to facilitate behavior adoption in urban-poor communities of Liberia for sustained COVID-19 suppression

BACKGROUND

Long-term suppression of SARS-CoV-2 transmission will involve strategies that recognize the heterogeneous capacity of communities to undertake public health recommendations. We highlight the epidemiological impact of barriers to adoption and the potential role of community-led coordination of support for cases and high-risk contacts in urban slums.

METHODS

A compartmental model representing transmission of SARS-CoV-2 in urban poor versus less socioeconomically vulnerable subpopulations was developed for Montserrado County, Liberia. Adoption of home-isolation behavior was assumed to be related to the proportion of each subpopulation residing in housing units with multiple rooms and with access to sanitation, water, and food. We evaluated the potential impact of increasing the maximum attainable proportion of adoption among urban poor following the scheduled lifting of the state of emergency.

RESULTS

Without intervention, the model estimated higher overall infection burden but fewer severe cases among urban poor versus the less socioeconomically vulnerable population. With self-isolation by mildly symptomatic individuals, median reductions in cumulative infections, severe cases, and maximum daily incidence were 7.6% (IQR: 2.2%-20.9%), 7.0% (2.0%-18.5%), and 9.9% (2.5%-31.4%), respectively, in the urban poor subpopulation and 16.8% (5.5%-29.3%), 15.0% (5.0%-26.4%), and 28.1% (9.3%-47.8%) in the less socioeconomically vulnerable population. An increase in the maximum attainable percentage of behavior adoption by the urban slum subpopulation was associated with median reductions of 19.2% (10.1%-34.0%), 21.1% (13.3%-34.2%), and 26.0% (11.5%-48.9%) relative to the status quo scenario.

CONCLUSIONS

Post-lockdown recommendations that prioritize home-isolation by confirmed cases are limited by resource constraints. Investing in community-based initiatives that coordinate support for self-identified cases and their contacts could more effectively suppress COVID-19 in settings with socioeconomic vulnerabilities.

Characteristics of the 100 largest modern zoonotic disease outbreaks

Zoonotic disease outbreaks are an important threat to human health and numerous drivers have been recognized as contributing to their increasing frequency. Identifying and quantifying relationships between drivers of zoonotic disease outbreaks and outbreak severity is critical to developing targeted zoonotic disease surveillance and outbreak prevention strategies. However, quantitative studies of outbreak drivers on a global scale are lacking. Attributes of countries such as press freedom, surveillance capabilities and latitude also bias global outbreak data. To illustrate these issues, we review the characteristics of the 100 largest outbreaks in a global dataset (n = 4463 bacterial and viral zoonotic outbreaks), and compare them with 200 randomly chosen background controls. Large outbreaks tended to have more drivers than background outbreaks and were related to large-scale environmental and demographic factors such as changes in vector abundance, human population density, unusual weather conditions and water contamination. Pathogens of large outbreaks were more likely to be viral and vector-borne than background outbreaks. Overall, our case study shows that the characteristics of large zoonotic outbreaks with thousands to millions of cases differ consistently from those of more typical outbreaks. We also discuss the limitations of our work, hoping to pave the way for more comprehensive future studies. This article is part of the theme issue 'Infectious disease macroecology: parasite diversity and dynamics across the globe'.

Interruption of tuberculosis detection and care during the Ebola virus disease epidemic (2014-2015) in Liberia: time-series analyses for 2013-2017

OBJECTIVE

Interrupted time-series analyses, using 5 years of routinely collected health information system data, were conducted to estimate the magnitude of impact of the 2014-2015 Ebola virus disease (EVD) epidemic and determine trends in tuberculosis (TB) care services in Liberia.

METHODS

A segmented linear regression model was used to generate estimates and predictions for trends for three TB service indicators before, during, and after EVD, from January 2013 to December 2017.

RESULTS

It was found that the number of presumptive TB cases declined significantly at the start of the EVD outbreak, with an estimated loss of 3222 cases (95% confidence interval (CI) -5691 to -752; P = 0.014). There was also an estimated loss of 709 cases per quarter post-EVD (95% CI -1346 to -71; P = 0.032). However, over the post-EVD period, quarterly increases were observed in the proportion of smear-positive to presumptive cases (1.45%, 95% CI 0.38% to 2.5%; P = 0.011) and the proportion of treatment success to TB cases evaluated (3.3%, 95% CI 0.82% to 5.79%; P = 0.013).

CONCLUSIONS

These findings suggest that the EVD outbreak (2014-2015) negatively affected TB care services. Rigorous quantitative analyses can be used to assess the magnitude of interruption and advocate for preparedness in settings with limited healthcare capacity.

Exploring the impacts of COVID-19 on Rohingya adolescents in Cox's Bazar: A mixed-methods study

This article explores how intersecting vulnerabilities faced by Rohingya adolescents living in Cox's Bazar, Bangladesh, have been exacerbated during the COVID-19 pandemic. Both the direct health impacts and the indirect repercussions of COVID-19 mitigation strategies have served to heighten pre-existing risks, preventing adolescents from reaching their full capabilities. This article provides empirical mixed-methods data from the Gender and Adolescence: Global Evidence (GAGE) longitudinal study, drawing on phone surveys adolescents aged 10-14 and 15-19 (1,761), qualitative interviews with adolescents aged 15-19 years (30), and key informant interviews (7) conducted between March and August 2020 with both Rohingya and Bangladeshi adolescents residing in refugee camps and host communities, respectively. While this article focuses on displaced Rohingya adolescents' experiences during COVID-19, we contextualize our findings by drawing on data collected from Bangladeshi adolescents who serve as comparators. Findings highlight that the pandemic has lead to a decline in Rohingya adolescents' reported health status, exacerbated food insecurity, educational and economic marginalization and bodily integrity risks, amongst both girls and boys. This paper concludes by reflecting on the policy implications necessary to safeguard refugee adolescent trajectories in the context of COVID-19.

Impact of Covid-19 on Transgender Persons: The Need for an Inclusive Approach

Objectives

The Covid-19 pandemic created significant impact and challenges particularly for vulnerable persons like transgender individuals worsening the prevailing stigma, discrimination, and exclusions against them. This review intends to assimilate the literature on the outbreak of Covid-19 and its impacts on transgender individuals across the world.

Methods

A narrative literature review on the impact of the Covid-19 pandemic among transgender persons has been done.

Results

This review reveals that transgender persons face exclusive structural, interpersonal, and personal risks from this pandemic and its response measures, endangering their lives, livelihoods, economy, health, and wellbeing.

Conclusions

Findings point to the need to design proactive and multi-level interventions that are sensitive to the unique needs of transgender individuals.

COVID-19 in patients with and without cancer: Examining differences in patient characteristics and outcomes

This study examines differences between patients with and without cancer in patient demographic and clinical characteristics and COVID-19 mortality and discusses the implications of these differences in relation to existing cancer disparities and COVID-19 vulnerabilities. Data was collected as a part of a retrospective study on a cohort of COVID-19 positive patients across Mount Sinai Health System from March 28, 2020 to April 26, 2020. Descriptive, comparative, and regression analyses were applied to examine differences between patients with and without cancer in demographic and clinical characteristics and COVID-19 mortality and whether cancer status predicts COVID-19 mortality controlling for these covariates using SAS 9.4. Results showed that, of 4641 patients who tested positive for COVID-19, 5.1% (N=236) had cancer. The median age of the total sample was 58 years (Q1-Q3: 41-71); 55.3% were male, 19.2% were current/former smokers, 6.1% were obese. The most commonly reported comorbidities were hypertension (22.6%) and diabetes (16.0%). Overall, the COVID-19 mortality rate was 8.3%. Examining differences between COVID-19 patients with and without cancer revealed significant differences (p<0.05) in COVID-19 mortality, hospitalization rates, age, gender, race, smoking status, obesity, and comorbidity indicators (e.g., diabetes) with cancer patients more likely to be older, male, black, obese, smokers, and with existing comorbidities. Controlling for these clinical, demographic, and behavioral characteristics, results of logistic regression analyses showed significant effects of older age and male gender on COVID-19 mortality (p<0.05). While cancer patients with COVID-19 were more likely to experience worse COVID-19 outcomes, these associations might be related to common cancer and COVID-19 vulnerability factors such as older age and gender. The coexistence of these vulnerability age and gender factors in both cancer and COVID-19 populations emphasizes the need for better understanding of their implications for cancer and COVID-19 disparities, both diseases prevention efforts, policies, and clinical management.

Mitigating the impact of COVID-19 on tuberculosis and HIV services: A cross-sectional survey of 669 health professionals in 64 low and middle-income countries

Objective

The experiences of frontline healthcare professionals are essential in identifying strategies to mitigate the disruption to healthcare services caused by the COVID-19 pandemic.

Methods

We conducted a cross-sectional study of TB and HIV professionals in low and middle-income countries (LMIC). Between May 12 and August 6, 2020, we collected qualitative and quantitative data using an online survey in 11 languages. We used descriptive statistics and thematic analysis to analyse responses.

Findings

669 respondents from 64 countries completed the survey. Over 40% stated that it was either impossible or much harder for TB and HIV patients to reach healthcare facilities since COVID-19. The most common barriers reported to affect patients were: fear of getting infected with SARS-CoV-2, transport disruptions and movement restrictions. 37% and 28% of responses about TB and HIV stated that healthcare provider access to facilities was also severely impacted. Strategies to address reduced transport needs and costs–including proactive coordination between the health and transport sector and cards that facilitate lower cost or easier travel—were presented in qualitative responses. Access to non-medical support for patients, such as food supplementation or counselling, was severely disrupted according to 36% and 31% of HIV and TB respondents respectively; qualitative data suggested that the need for such services was exacerbated.

Conclusion

Patients and healthcare providers across numerous LMIC faced substantial challenges in accessing healthcare facilities, and non-medical support for patients was particularly impacted. Synthesising recommendations of frontline professionals should be prioritised for informing policymakers and healthcare service delivery organisations.

Gendered care at the margins: Ebola, gender, and caregiving practices in Uganda's border districts

In July 2019, Ebola in the Democratic Republic of Congo (DRC) was declared a public health emergency of international concern and neighbouring countries were put on high alert. This paper examines the intersections of gender, caregiving, and livelihood practices in Uganda's border districts that emerged as key factors to consider in preparedness and response. This paper is based on an anthropological study of the Ebola context among Bantu cultures. We report on data from focus group discussions and key informant interviews with various sectors of the community. The study identified intersecting themes reported here: (1) women as primary caregivers in this context; and (2) women as providers, often in occupations that increase vulnerability to Ebola. Findings demonstrate the role that women play inside and outside the home as caregivers of the sick and during burials, and intersections with livelihood-seeking strategies. Because women's caregiving is largely unpaid, women face a double burden of work as they seek other livelihood strategies that sometimes increase vulnerability to Ebola. Epidemic response should address these intersections and the context-specific vulnerabilities of caregivers; it should also be localised and community-centred and able to attend to the cultural as well as the economic needs of a community.

Social determinants of mortality from COVID-19: A simulation study using NHANES

BACKGROUND

The COVID-19 epidemic in the United States is widespread, with more than 200,000 deaths reported as of September 23, 2020. While ecological studies show higher burdens of COVID-19 mortality in areas with higher rates of poverty, little is known about social determinants of COVID-19 mortality at the individual level.

METHODS AND FINDINGS

We estimated the proportions of COVID-19 deaths by age, sex, race/ethnicity, and comorbid conditions using their reported univariate proportions among COVID-19 deaths and correlations among these variables in the general population from the 2017-2018 National Health and Nutrition Examination Survey (NHANES). We used these proportions to randomly sample individuals from NHANES. We analyzed the distributions of COVID-19 deaths by race/ethnicity, income, education level, and veteran status. We analyzed the association of these characteristics with mortality by logistic regression. Summary demographics of deaths include mean age 71.6 years, 45.9% female, and 45.1% non-Hispanic white. We found that disproportionate deaths occurred among individuals with nonwhite race/ethnicity (54.8% of deaths, 95% CI 49.0%-59.6%, p < 0.001), individuals with income below the median (67.5%, 95% CI 63.4%-71.5%, p < 0.001), individuals with less than a high school level of education (25.6%, 95% CI 23.4% -27.9%, p < 0.001), and veterans (19.5%, 95% CI 15.8%-23.4%, p < 0.001). Except for veteran status, these characteristics are significantly associated with COVID-19 mortality in multiple logistic regression. Limitations include the lack of institutionalized people in the sample (e.g., nursing home residents and incarcerated persons), the need to use comorbidity data collected from outside the US, and the assumption of the same correlations among variables for the noninstitutionalized population and COVID-19 decedents.

CONCLUSIONS

Substantial inequalities in COVID-19 mortality are likely, with disproportionate burdens falling on those who are of racial/ethnic minorities, are poor, have less education, and are veterans. Healthcare systems must ensure adequate access to these groups. Public health measures should specifically reach these groups, and data on social determinants should be systematically collected from people with COVID-19.

The Impact of Different Types of Violence on Ebola Virus Transmission During the 2018-2020 Outbreak in the Democratic Republic of the Congo

BACKGROUND

Our understanding of the different effects of targeted versus nontargeted violence on Ebola virus (EBOV) transmission in Democratic Republic of the Congo (DRC) is limited.

METHODS

We used time-series data of case counts to compare individuals in Ebola-affected health zones in DRC, April 2018-August 2019. Exposure was number of violent events per health zone, categorized into Ebola-targeted or Ebola-untargeted, and into civilian-induced, (para)military/political, or protests. Outcome was estimated daily reproduction number (Rt) by health zone. We fit linear time-series regression to model the relationship.

RESULTS

Average Rt was 1.06 (95% confidence interval [CI], 1.02-1.11). A mean of 2.92 violent events resulted in cumulative absolute increase in Rt of 0.10 (95% CI, .05-.15). More violent events increased EBOV transmission (P = .03). Considering violent events in the 95th percentile over a 21-day interval and its relative impact on Rt, Ebola-targeted events corresponded to Rt of 1.52 (95% CI, 1.30-1.74), while civilian-induced events corresponded to Rt of 1.43 (95% CI, 1.21-1.35). Untargeted events corresponded to Rt of 1.18 (95% CI, 1.02-1.35); among these, militia/political or ville morte events increased transmission.

CONCLUSIONS

Ebola-targeted violence, primarily driven by civilian-induced events, had the largest impact on EBOV transmission.

The socio-economic distribution of exposure to Ebola: Survey evidence from Liberia and Sierra Leone

Socio-economic factors are widely believed to have been an important driver of the transmission of Ebola Virus Disease (EVD) during the West African outbreak of 2014–16, however, studies that have investigated the relationship between socio-economic status (SES) and EVD have found inconsistent results. Using nationally representative household survey data on whether respondents knew a close friend or family member with Ebola, we explore the SES determinants of EVD exposure along individual, household, and community lines in Liberia and Sierra Leone. While we find no overall association between household wealth and EVD exposure, we find that pooled data mask important differences observed within countries with higher wealth households more likely to have been exposed to EVD in Sierra Leone and the opposite relationship in Liberia. Finally, we also generally find a positive association between education and EVD exposure both at the individual and the community levels in the full sample. There is an urgent need to better understand these relationships to examine both why the outbreak spread and to help prepare for future outbreaks.

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Socio-economic status (SES) was believed to be an important driver of exposure Ebola in the West African outbreak.

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Previous studies of the relationship between SES and Ebola show inconsistent associations.

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We find that higher wealth households were more likely to be exposed to Ebola in Sierra Leone but not Liberia.

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We also find higher SES communities were less likely to have been exposed.

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We also find a positive association with education at the individual and community levels.

Understanding the slum-health conundrum in sub-Saharan Africa: a proposal for a rights-based approach to health promotion in slums

Sub-Saharan Africa is the world's least urbanized region but is ironically also the region with the largest proportion of urban slum dwellers. However, there exists limited understanding of the impact of slums on health in the region. To address this knowledge gap, we conducted a systematic search in PubMed, Google, and Google Scholar to identify and review studies examining the slum-health relationship in sub-Saharan African cities. Subsequently, we performed thematic analysis of 40 studies to identify themes that explain the health impact of slums in the region. The majority of studies characterize slums as health-damaging settings, where poverty and unfavorable environmental conditions pose threats to public health and safety. Only a handful of studies suggest a beneficial relationship between slums and health, in such areas as affordable housing provision, employment generation, and community cohesion. We argue that the literature's overwhelming emphasis on the environmental risks of slums feeds into a neoliberal urban agenda that seeks to clear slums at the expense of their beneficial contributions to health. Accordingly, we advocate a shift in policy discourse, from static characterization of slums as health risks to a health-promotion agenda that emphasizes the housing and service rights of slum populations.

Ebola vaccination in the Democratic Republic of the Congo

Following the April 2018 reemergence of Ebola in a rural region of the Democratic Republic of the Congo (DRC), the virus spread to an urban center by early May. Within 2 wk of the first case confirmation, a vaccination campaign was initiated in which 3,017 doses were administered to contacts of cases and frontline healthcare workers. To evaluate the spatial dynamics of Ebola transmission and quantify the impact of vaccination, we developed a geographically explicit model that incorporates high-resolution data on poverty and population density. We found that while Ebola risk was concentrated around sites initially reporting infections, longer-range dissemination also posed a risk to areas with high population density and poverty. We estimate that the vaccination program contracted the geographical area at risk for Ebola by up to 70.4% and reduced the level of risk within that region by up to 70.1%. The early implementation of vaccination was critical. A delay of even 1 wk would have reduced these effects to 33.3 and 44.8%, respectively. These results underscore the importance of the rapid deployment of Ebola vaccines during emerging outbreaks to containing transmission and preventing global spread. The spatiotemporal framework developed here provides a tool for identifying high-risk regions, in which surveillance can be intensified and preemptive control can be implemented during future outbreaks.

Population mobility reductions associated with travel restrictions during the Ebola epidemic in Sierra Leone: use of mobile phone data

Background

Travel restrictions were implemented on an unprecedented scale in 2015 in Sierra Leone to contain and eliminate Ebola virus disease. However, the impact of epidemic travel restrictions on mobility itself remains difficult to measure with traditional methods. New 'big data' approaches using mobile phone data can provide, in near real-time, the type of information needed to guide and evaluate control measures.

Methods

We analysed anonymous mobile phone call detail records (CDRs) from a leading operator in Sierra Leone between 20 March and 1 July in 2015. We used an anomaly detection algorithm to assess changes in travel during a national 'stay at home' lockdown from 27 to 29 March. To measure the magnitude of these changes and to assess effect modification by region and historical Ebola burden, we performed a time series analysis and a crossover analysis.

Results

Routinely collected mobile phone data revealed a dramatic reduction in human mobility during a 3-day lockdown in Sierra Leone. The number of individuals relocating between chiefdoms decreased by 31% within 15 km, by 46% for 15-30 km and by 76% for distances greater than 30 km. This effect was highly heterogeneous in space, with higher impact in regions with higher Ebola incidence. Travel quickly returned to normal patterns after the restrictions were lifted.

Conclusions

The effects of travel restrictions on mobility can be large, targeted and measurable in near real-time. With appropriate anonymization protocols, mobile phone data should play a central role in guiding and monitoring interventions for epidemic containment.

The Politics of Disease Epidemics: a Comparative Analysis of the SARS, Zika, and Ebola Outbreaks

Over the past few decades, disease outbreaks have become increasingly frequent and widespread. The epicenters of these outbreaks have differed, and could be linked to different economic contexts. Arguably, the responses to these outbreaks have been "political" and inherently burdensome to marginalized populations. Key lessons can be learned from exploring the narratives about the different epidemics in varying income settings. Based on a review of the published medical, social, and political literature, which was accessed using four electronic databases-PubMed, Sociological Abstracts, Scholars Portal, and Web of Science, the overall objective of this paper discuss scholars' narratives on the "politics" of Ebola in a low-income setting, Zika virus in a middle-income setting, and SARS in a high-income setting. Various themes of the politics of epidemics were prominent in the literature. The narratives demonstrated the influence of power in whose narratives and what narratives are presented in the literature. While marginalized populations were reported to have borne the brunt of all disease outbreaks in the different contexts, the prevalence of their narratives within the reviewed literature was limited. Regardless of income setting, there is a need to give voice to the most marginalized communities during an epidemic. The experiences and narratives of those most vulnerable to an epidemic-specifically poor communities-need to be represented in the literature. This could contribute to mitigating some of the negative impact of the politics in epidemics.

Priority setting for disease outbreaks in Uganda: A case study evaluating the process

Priority setting (PS) and resource allocation during health emergencies are key factors influencing an effective response. However, there is limited understanding of how priorities and resource allocation during disease outbreaks occur and the extent to which these processes are successful. This paper, based on 23 in-depth interviews with policy makers and a review of policy and emergency preparedness documents, used a PS evaluation framework to evaluate PS for disease outbreaks in Uganda. With regard to PS for disease outbreaks in Uganda, we identified a conducive socio-political-economical context, credible institutions, formal participatory prioritisation processes, evidence informed the processes, demonstrated implementation capacity, institutional strengthening and positive health outcomes. Factors that compromised the success of PS included limited resources - especially in between disease outbreaks and unfair processes. Investment in sustaining the established prioritisation infrastructure to oversee preparedness activities between the outbreaks would strengthen the prioritisation process. This should be supported with health system strengthening. The framework enabled us to evaluate some aspects of PS during disease outbreaks. The framework's inability to evaluate all aspects, and reported as opposed to actual PS calls for the integration of evaluation throughout the planning and implementation process to ensure validity and continuous implementation of improvement strategies.

Potential for broad-scale transmission of Ebola virus disease during the West Africa crisis: lessons for the Global Health security agenda

Background

The 2014–2016 Ebola crisis in West Africa had approximately eight times as many reported deaths as the sum of all previous Ebola outbreaks. The outbreak magnitude and occurrence of multiple Ebola cases in at least seven countries beyond Liberia, Sierra Leone, and Guinea, hinted at the possibility of broad-scale transmission of Ebola.

Main text

Using a modeling tool developed by the US Centers for Disease Control and Prevention during the Ebola outbreak, we estimated the number of Ebola cases that might have occurred had the disease spread beyond the three countries in West Africa to cities in other countries at high risk for disease transmission (based on late 2014 air travel patterns). We estimated Ebola cases in three scenarios: a delayed response, a Liberia-like response, and a fast response scenario. Based on our estimates of the number of Ebola cases that could have occurred had Ebola spread to other countries beyond the West African foci, we emphasize the need for improved levels of preparedness and response to public health threats, which is the goal of the Global Health Security Agenda. Our estimates suggest that Ebola could have potentially spread widely beyond the West Africa foci, had local and international health workers and organizations not committed to a major response effort. Our results underscore the importance of rapid detection and initiation of an effective, organized response, and the challenges faced by countries with limited public health systems. Actionable lessons for strengthening local public health systems in countries at high risk of disease transmission include increasing health personnel, bolstering primary and critical healthcare facilities, developing public health infrastructure (e.g. laboratory capacity), and improving disease surveillance. With stronger local public health systems infectious disease outbreaks would still occur, but their rapid escalation would be considerably less likely, minimizing the impact of public health threats such as Ebola.

Conclusions

The Ebola outbreak could have potentially spread to other countries, where limited public health surveillance and response capabilities may have resulted in additional foci. Health security requires robust local health systems that can rapidly detect and effectively respond to an infectious disease outbreak.

Electronic supplementary material

The online version of this article (10.1186/s40249-017-0373-4) contains supplementary material, which is available to authorized users.

Analysis of patient data from laboratories during the Ebola virus disease outbreak in Liberia, April 2014 to March 2015

An outbreak of Ebola virus disease (EVD) in Liberia began in March 2014 and ended in January 2016. Epidemiological information on the EVD cases was collected and managed nationally; however, collection and management of the data were challenging at the time because surveillance and reporting systems malfunctioned during the outbreak. EVD diagnostic laboratories, however, were able to register basic demographic and clinical information of patients more systematically. Here we present data on 16,370 laboratory samples that were tested between April 4, 2014 and March 29, 2015. A total of 10,536 traceable individuals were identified, of whom 3,897 were confirmed cases (positive for Ebola virus RNA). There were significant differences in sex, age, and place of residence between confirmed and suspected cases that tested negative for Ebola virus RNA. Age (young children and the elderly) and place of residence (rural areas) were the risk factors for death due to the disease. The case fatality rate of confirmed cases decreased from 80% to 63% during the study period. These findings may help support future investigations and lead to a fuller understanding of the outbreak in Liberia.

Characterizing risk of Ebola transmission based on frequency and type of case-contact exposures

During the initial months of the 2013-2016 Ebola epidemic, rapid geographical dissemination and intense transmission challenged response efforts across West Africa. Contextual behaviours associated with increased risk of exposure included travel to high-transmission settings, caring for sick and preparing the deceased for traditional funerals. Although such behaviours are widespread in West Africa, high-transmission pockets were observed. Superspreading and clustering are typical phenomena in infectious disease outbreaks, as a relatively small number of transmission chains are often responsible for the majority of events. Determining the characteristics of contacts at greatest risk of developing disease and of cases with greatest transmission potential could therefore help curb propagation of infection. Our analysis of contact tracing data from Montserrado County, Liberia, suggested that the probability of transmission was 4.5 times higher for individuals who were reported as having contact with multiple cases. The probability of individuals developing disease was not significantly associated with age or sex of their source case but was higher when they were in the same household as the infectious case. Surveillance efforts for rapidly identifying symptomatic individuals and effectively messaged campaigns encouraging household members to bring the sick to designated treatment centres without administration of home care could mitigate transmission.This article is part of the themed issue 'The 2013-2016 West African Ebola epidemic: data, decision-making and disease control'.

The socio-economic drivers of bushmeat consumption during the West African Ebola crisis

Bushmeat represents an important source of animal protein for humans in tropical Africa. Unsustainable bushmeat hunting is a major threat to wildlife and its consumption is associated with an increased risk of acquiring zoonotic diseases, such as Ebola virus disease (EVD). During the recent EVD outbreak in West Africa, it is likely that human dietary behavior and local attitudes toward bushmeat consumption changed in response to the crisis, and that the rate of change depended on prevailing socio-economic conditions, including wealth and education. In this study, we therefore investigated the effects of income, education, and literacy on changes in bushmeat consumption during the crisis, as well as complementary changes in daily meal frequency, food diversity and bushmeat preference. More specifically, we tested whether wealthier households with more educated household heads decreased their consumption of bushmeat during the EVD crisis, and whether their daily meal frequency and food diversity remained constant. We used Generalized Linear Mixed Models to analyze interview data from two nationwide household surveys across Liberia. We found an overall decrease in bushmeat consumption during the crisis across all income levels. However, the rate of bushmeat consumption in high-income households decreased less than in low-income households. Daily meal frequency decreased during the crisis, and the diversity of food items and preferences for bushmeat species remained constant. Our multidisciplinary approach to study the impact of EVD can be applied to assess how other disasters affect social-ecological systems and improve our understanding and the management of future crises.

The consumption of wild animal meat, commonly known as bushmeat, is widespread throughout tropical regions. Bushmeat provides an essential source of protein and income for human livelihoods. However, its consumption is linked to the transmission of zoonotic diseases, such as Ebola, and its over-harvest is a major threat to many wildlife species. The bushmeat trade therefore encompasses a broad range of socio-economic and ecological issues. As such, we think it is highly important to use an interdisciplinary approach to investigate the drivers of bushmeat consumption, to improve our understanding and management of future crises. Our analysis of household interview data collected during two surveys across Liberia shows that there was an overall decrease in bushmeat consumption during the recent Ebola crisis. However, the consumption of bushmeat in wealthier households decreased less than in poorer households. In addition, we found that daily meal frequency decreased during the crisis, and the diversity of food items and preferences for bushmeat species remained constant.

Predicting Ebola infection: A malaria-sensitive triage score for Ebola virus disease

Background

The non-specific symptoms of Ebola Virus Disease (EVD) pose a major problem to triage and isolation efforts at Ebola Treatment Centres (ETCs). Under the current triage protocol, half the patients allocated to high-risk “probable” wards were EVD(-): a misclassification speculated to predispose nosocomial EVD infection. A better understanding of the statistical relevance of individual triage symptoms is essential in resource-poor settings where rapid, laboratory-confirmed diagnostics are often unavailable.

Methods/Principal findings

This retrospective cohort study analyses the clinical characteristics of 566 patients admitted to the GOAL-Mathaska ETC in Sierra Leone. The diagnostic potential of each characteristic was assessed by multivariate analysis and incorporated into a statistically weighted predictive score, designed to detect EVD as well as discriminate malaria. Of the 566 patients, 28% were EVD(+) and 35% were malaria(+). Malaria was 2-fold more common in EVD(-) patients (p<0.05), and thus an important differential diagnosis. Univariate analyses comparing EVD(+) vs. EVD(-) and EVD(+)/malaria(-) vs. EVD(-)/malaria(+) cohorts revealed 7 characteristics with the highest odds for EVD infection, namely: reported sick-contact, conjunctivitis, diarrhoea, referral-time of 4–9 days, pyrexia, dysphagia and haemorrhage. Oppositely, myalgia was more predictive of EVD(-) or EVD(-)/malaria(+). Including these 8 characteristics in a triage score, we obtained an 89% ability to discriminate EVD(+) from either EVD(-) or EVD(-)/malaria(+).

Conclusions/Significance

This study proposes a highly predictive and easy-to-use triage tool, which stratifies the risk of EVD infection with 89% discriminative power for both EVD(-) and EVD(-)/malaria(+) differential diagnoses. Improved triage could preserve resources by identifying those in need of more specific differential diagnostics as well as bolster infection prevention/control measures by better compartmentalizing the risk of nosocomial infection.

Four decades after the discovery of Ebola virus disease (EVD), the sources, reservoirs and dynamics of infection are still largely unknown and thus the threat of re-emergence remains ever present. As EVD thrives on fragile healthcare systems in the developing world, it is essential that triage tools are low-cost and easy-to-use in order to best allocate limited resources and ensure sustainability of EVD surveillance. From a public health perspective, sensitivity is paramount when screening for highly contagious and fatal diseases such as Ebola. However, once these suspect patients arrive at the treatment centres, specificity becomes far more important in order to accurately allocate them to risk-appropriate wards and better distribute limited resources. Currently, pre-test triage to identify “suspect” Ebola patients consists of a binary evaluation of non-specific symptoms that are shared by the much more prevalent disease: Malaria. Using these guidelines, over 70% of patients selected for admission to the potentially contagious environment of an ETC did not have Ebola. Within the ETC, patients may be further triaged into a higher risk “probable” ward on the basis of a clinically subjective assessment known as the “Ebola look”: since proven to have comparable accuracy to flipping a coin. While compartmentalising risk by stratification is an essential component to infection prevention and control measures, patient triage should be sufficiently accurate to justify to its benefit. This study constructs an easy-to-use and highly accurate (90%) triage scoring system that discriminates EVD infection risk in a malaria-sensitive manner: a strategy, which not only significantly improves the predictive accuracy for EVD but may also identify the (more deadly) infection of malaria.

Public health and public trust: Survey evidence from the Ebola Virus Disease epidemic in Liberia

Trust in government has long been viewed as an important determinant of citizens' compliance with public health policies, especially in times of crisis. Yet evidence on this relationship remains scarce, particularly in the developing world. We use results from a representative survey conducted during the 2014-15 Ebola Virus Disease (EVD) epidemic in Monrovia, Liberia to assess the relationship between trust in government and compliance with EVD control interventions. We find that respondents who expressed low trust in government were much less likely to take precautions against EVD in their homes, or to abide by government-mandated social distancing mechanisms designed to contain the spread of the virus. They were also much less likely to support potentially contentious control policies, such as "safe burial" of EVD-infected bodies. Contrary to stereotypes, we find no evidence that respondents who distrusted government were any more or less likely to understand EVD's symptoms and transmission pathways. While only correlational, these results suggest that respondents who refused to comply may have done so not because they failed to understand how EVD is transmitted, but rather because they did not trust the capacity or integrity of government institutions to recommend precautions and implement policies to slow EVD's spread. We also find that respondents who experienced hardships during the epidemic expressed less trust in government than those who did not, suggesting the possibility of a vicious cycle between distrust, non-compliance, hardships and further distrust. Finally, we find that respondents who trusted international non-governmental organizations (INGOs) were no more or less likely to support or comply with EVD control policies, suggesting that while INGOs can contribute in indispensable ways to crisis response, they cannot substitute for government institutions in the eyes of citizens. We conclude by discussing the implications of our findings for future public health crises.

Effect of modelling slum populations on influenza spread in Delhi

OBJECTIVES

This research studies the impact of influenza epidemic in the slum and non-slum areas of Delhi, the National Capital Territory of India, by taking proper account of slum demographics and residents' activities, using a highly resolved social contact network of the 13.8 million residents of Delhi.

METHODS

An SEIR model is used to simulate the spread of influenza on two different synthetic social contact networks of Delhi, one where slums and non-slums are treated the same in terms of their demographics and daily sets of activities and the other, where slum and non-slum regions have different attributes.

RESULTS

Differences between the epidemic outcomes on the two networks are large. Time-to-peak infection is overestimated by several weeks, and the cumulative infection rate and peak infection rate are underestimated by 10-50%, when slum attributes are ignored.

CONCLUSIONS

Slum populations have a significant effect on influenza transmission in urban areas. Improper specification of slums in large urban regions results in underestimation of infections in the entire population and hence will lead to misguided interventions by policy planners.

Exposure-Specific and Age-Specific Attack Rates for Ebola Virus Disease in Ebola-Affected Households, Sierra Leone

Using histories of household members of Ebola virus disease (EVD) survivors in Sierra Leone, we calculated risk of EVD by age and exposure level, adjusting for confounding and clustering, and estimated relative risks. Of 937 household members in 94 households, 448 (48%) had had EVD. Highly correlated with exposure, EVD risk ranged from 83% for touching a corpse to 8% for minimal contact and varied by age group: 43% for children <2 years of age; 30% for those 5-14 years of age; and >60% for adults >30 years of age. Compared with risk for persons 20-29 years of age, exposure-adjusted relative risks were lower for those 5-9 (0.70), 10-14 (0.64), and 15-19 (0.71) years of age but not for children <2 (0.92) or 2-4 (0.97) years of age. Lower risk for 5-19-year-olds, after adjustment for exposure, suggests decreased susceptibility in this group.

Heterogeneity in District-Level Transmission of Ebola Virus Disease during the 2013-2015 Epidemic in West Africa

The Ebola virus disease (EVD) epidemic in West Africa in 2013-2015 spread heterogeneously across the three hardest-hit countries Guinea, Liberia and Sierra Leone and the estimation of national transmission of EVD provides little information about local dynamics. To investigate district-level transmissibility of EVD, we applied a statistical modelling approach to estimate the basic reproduction number (R0) for each affected district and each country using weekly incident case numbers. We estimated growth rates during the early exponential phase of the outbreak using exponential regression of the case counts on the first eight weeks since onset. To take into account the heterogeneity between and within countries, we fitted a mixed effects model and calculated R0 based on the predicted individual growth rates and the reported serial interval distribution. At district level, R0 ranged from 0.36 (Dubréka) to 1.72 (Beyla) in Guinea, from 0.53 (Maryland) to 3.37 (Margibi) in Liberia and from 1.14 (Koinadugu) to 2.73 (Western Rural) in Sierra Leone. At national level, we estimated an R0 of 0.97 (95% CI 0.77-1.18) for Guinea, 1.26 (95% CI 0.98-1.55) for Liberia and 1.66 (95% CI 1.32-2.00) for Sierra Leone. Socio-demographic variables related to urbanisation such as high population density and high wealth index were found positively associated with R0 suggesting that the consequences of fast urban growth in West Africa may have contributed to the increased spread of EVD.

Deaths, late deaths, and role of infecting dose in Ebola virus disease in Sierra Leone: retrospective cohort study

OBJECTIVES

 To assess the frequency of fatal recrudescence from Ebola virus disease after discharge from treatment centres, and explore the influence of infecting dose on case fatality rates.

DESIGN

 Retrospective cohort study.

SETTING

 Western Area, Sierra Leone.

PARTICIPANTS

 151 survivors treated for Ebola virus disease at the Kerry Town treatment centre and discharged. Survivors were followed up for a vital status check at four to nine months after discharge, and again at six to 13 months after discharge. Verbal autopsies were conducted for four survivors who had died since discharge (that is, late deaths). Survivors still living in Western Area were interviewed together with their household members. Exposure level to Ebola virus disease was ascertained as a proxy of infecting dose, including for those who died.

MAIN OUTCOME MEASURES

 Risks and causes of late death; case fatality rates; odds ratios of death from Ebola virus disease by age, sex, exposure level, date, occupation, and household risk factors.

RESULTS

 Follow-up information was obtained on all 151 survivors of Ebola virus disease, a mean of 10 months after discharge. Four deaths occurred after discharge, all within six weeks: two probably due to late complications, one to prior tuberculosis, and only one after apparent full recovery, giving a maximum estimate of recrudescence leading to death of 0.7%. In these households, 395 people were reported to have had Ebola virus disease, of whom 227 died. A further 53 people fulfilled the case definition for probable disease, of whom 11 died. Therefore, the case fatality rate was 57.5% (227/395) for reported Ebola virus disease, or 53.1% (238/448) including probable disease. Case fatality rates were higher in children aged under 2 years and adults older than 30 years, in larger households, and in infections occurring earlier in the epidemic in Sierra Leone. There was no consistent trend of case fatality rate with exposure level, although increasing exposure increased the risk of Ebola virus disease.

CONCLUSIONS

 In this study of survivors in Western Area, Sierra Leone, late recrudescence of severe Ebola virus disease appears to be rare. There was no evidence for an effect of infecting dose (as measured by exposure level) on the severity of disease.

Bibliometric analysis of medicine-related publications on poverty (2005-2015)

BACKGROUND

Poverty is a global problem. The war against poverty requires not only financial support, but also poverty-related research to pinpoint areas of high need of intervention. In line with international efforts to fight poverty and negative consequences, we carried out this study to give a bibliometric overview of medicine-related literature on poverty. Such a s study is an indicator of the extent of interaction of various international key players on the war against poverty-related health problems.

METHODS

Scopus was used to achieve the objective of this study. The time span set for this study was 2005-2015. Poverty-related articles under the subject area "Medicine" were used to give bibliometric indicators such as annual growth of publications, international collaboration, highly cited articles, active countries, institutions, journals, and authors.

RESULTS

The total number of retrieved articles was 1583. The Hirsh-index of retrieved articles was 56. A modest and fluctuating increase was seen over the study period. Visualization map of retrieved articles showed that "HIV", infectious diseases, mental health, India, and Africa were most commonly encountered terms. No significant dominance of any particular author or journal was observed in retrieved articles. The United States of America had the largest share in the number of published articles. The World Health Organization and Centers for Disease Prevention and Control were among top active institutions/organizations. International collaboration was observed in less than one third of publications. Top cited articles focused on three poverty-related health issues, mainly, infectious diseases, malnutrition, and child development/psychology. Most of top articles were published in high impact journals.

CONCLUSIONS

Data indicated that articles on poverty were published in high influential medical journals indicative of the importance of poverty as a global health problem. However, the number publications and the extent of international collaborations was lower than expected given the huge burden of poverty-related health problems.