Disparities in spread and control of influenza in slums of Delhi: findings from an agent-based modelling study

Health inequalities at the intersection of multiple social determinants among under five children residing Nairobi urban slums: An application of multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA)

In this analysis we examine through an intersectionality lens how key social determinants of health (SDOH) are associated with health conditions among under-five children (<5y) residing in Nairobi slums, Kenya. We used cross-sectional data collected from Nairobi slums between June and November 2012 to explore how multiple interactions of SDoH shape health inequalities in slums. We applied multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA) approach. We constructed intersectional strata for each health condition from combinations of significant SDoH obtained using univariate analyses. We then estimated the intersectional effects of health condition in a series of MAIHDA logistic regression models distinguishing between additive and interaction effects. We quantified discriminatory accuracy (DA) of the intersectional strata by means of the variance partitioning coefficient (VPC) and the area under the receiver operating characteristic curve (AUC-ROC). The total participants were 2,199 <5y, with 120 records (5.5%) dropped because health conditions were recorded as "not applicable". The main outcome variables were three health conditions: 1) whether a child had diarrhea or not, 2) whether a child had fever or not, and 3) whether a child had cough or not in the previous two weeks. We found non-significant intersectional effects for each health condition. The head of household ethnic group was significantly associated with each health condition. We found good DA for diarrhea (VPC = 9.0%, AUC-ROC = 76.6%) an indication of large intersectional effects. However, fever (VPC = 1.9%, AUC-ROC = 66.3%) and cough (VPC = 0.5%, AUC-ROC = 61.8%) had weak DA indicating existence of small intersectional effects. Our study shows pathways for SDoH that affect diarrhea, cough, and fever for <5y living in slums are multiplicative and shared. The findings show that <5y from Luo and Luhya ethnic groups, recent migrants (less than 2 years), and households experiencing CHE are more likely to face worse health outcomes. We recommend relevant stakeholders to develop strategies aimed at identifying these groups for targeted proportionate universalism based on the level of their need.

Vulnerability, neglect, and collectivity in Brazilian favelas: Surviving the threats of the COVID-19 pandemic and the state's necropolitics

The COVID-19 pandemic has deepened existing inequities and injustices in Brazil, seen in the disproportionately detrimental impacts on favelas. State policy responses to the pandemic have disregarded favela residents' experiences. Recommendations such as 'shelter-in-place' ignore the reality of over 11.4 million favela residents who cannot work from home or afford to stop working, nor practise physical distancing from others. This study investigates the discourse of community organisations in favelas as they respond to the threats of the COVID-19 pandemic and the state's necropolitics. Community organisations in favelas have taken action to protect their residents from the virus, unemployment and hunger. I assess organisations' (1) justification to act as a collective in their communities, and (2) stances about the government's responses to the crisis. Through content analysis of social media, websites and media appearances of eight favela organisations and collectives in São Paulo and Rio de Janeiro, this study finds three main themes through which organisations justify their actions: vulnerability, neglect, and collectivity and care. More than survival strategies, the actions of favela organisations are counter-political acts as they oppose the decrepit necropolitics of the state by collectively enduring in the Brazilian context of the COVID-19 pandemic. Understanding favela organisations' actions in response to the pandemic is fundamental. It further illuminates the impact of public health emergencies in the lives of informal settlements' residents and the governance of public health emergencies in these communities.

Differential impact of maternal education on under-five mortality in rural and urban India

Under-five mortality rate (U5MR) differs by rural-urban place of residence and mother's education; however, the rural-urban gap in U5MR by mother's educational attainment is unclear in the existing literature. Using five rounds of the national family health surveys (NFHS I-V) conducted between 1992-93 and 2019-21 in India, this study estimated the main and interaction effects of rural-urban and maternal education on U5MR. The mixed effect Cox proportional hazard (MECPH) model was used to predict the risk of under-five mortality (U5M). The finding shows that unadjusted U5MR remained 50 per cent higher in rural areas than in urban areas across the surveys. Whereas, after controlling for demographic, socioeconomic, and maternal health care predictors of U5M, the MECPH regression results indicated that urban children had a higher risk of death than their rural counterparts in NFHS I-III. However, there are no significant rural-urban differences in the last two surveys (NFHS IV -V). In addition, increasing maternal education levels were associated with lower U5M in all surveys. Though, in recent years, primary education has had no significant effect. The U5M risk was additionally lower for urban children than rural children whose mothers had secondary and higher education by NFHS-III; however, this additional urban advantage was no longer significant in recent surveys. The higher impact of secondary education on U5MR in urban areas in the past may be attributed to poor socio-economic, healthcare conditions in rural areas. Overall, maternal education, particularly secondary education, remained a protective factor for U5M in both rural and urban areas, even after controlling for predictors. Therefore, there is a need to increase the focus on secondary education for girls for a further decline in U5M.

An update of intestinal helminth infections among urban slum communities in Bangladesh

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Parasitic infections remain prevalent in urban slum communities in Bangladesh.

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School-aged children had a higher infection rate compared with adults.

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Ascaris lumbricoides was predominant in children, and hookworms were predominant in adults.

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Rhabditis sp. was observed for the first time in humans in Bangladesh.

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A significant association was found between free-roaming animals and human parasitic infections.

Aim

Methods

Results

Conclusion

Psychological determinants of COVID-19 vaccine acceptance among urban slum dwellers of Bangladesh

Introduction

Coronavirus disease 2019 (COVID-19) vaccination has emerged as a promising approach to counter the harmful impacts of the pandemic. Understanding the psychological components that may impact an individual's attitude toward COVID-19 vaccination is crucial for generating evidence-based ways to minimize vaccine hesitancy. This study determined the psychological antecedents regarding vaccine acceptance among urban slum people of Bangladesh.

Methods

From 5 July to 5 August 5, 2021, a face-to-face survey was conducted in the urban slum of two large cities in Bangladesh. The questionnaire considered socio-demographics, health-related characteristics, psychological determinants, sources of information, and conspiracy beliefs regarding COVID-19. The 5C sub-scales were used to assess psychological antecedents. Five stepwise binary logistic regression models evaluated significant predictors for confidence, complacency, calculation, constraints, and collective responsibility. Multinomial logistic regression was used to determine the relationship between psychological antecedents and vaccine acceptability.

Results

The study revealed that the slum residents with a high level of confident (89.94%), complacent (72.73%), having constraints (82.31%), calculative (84.80%), and responsible (93.30%) showed a higher vaccine acceptance rate. Higher vaccine acceptance was related to the believer in natural-made origin (85.96%) and those who rejected anti-vaccination (88.44%). The information acquired from newspapers differed significantly (p < 0.05), though TV or radio was the most common primary information source about COVID-19 vaccines (74.75%). The regression result revealed that marital status, education, family income, and perceived health condition were significantly associated with the 5C domains. Two psychological antecedents including complacency (OR = 3.97; p < 0.001) and collective responsibility (OR = 0.23; p < 0.001) were significantly associated with vaccine acceptance.

Conclusions

Different predictors significantly affect psychological antecedents related to COVID-19 vaccine uptake. Therefore, considering the factors, targeted actions based on the findings may help to lower vaccine reluctance and boost vaccination rates.

Health protection challenges of slums residents during the COVID-19 pandemic, according to the social determinants of health framework: A case study of Kerman city in Iran

BACKGROUND

Coronavirus disease-2019 (COVID-19) pandemic can aggravate the health problems in slum areas. The present study intends to examine the challenges of health protection of slum's residences during the COVID-19 pandemic with the Social Determinants of Health perspective, in Kerman city in Iran.

MATERIALS AND METHODS

The present study was a qualitative content analysis. Data were collected by purposeful sampling in-depth and semi-structured interviews with 16 people. The interviews were conducted (from October to December 2020) with the local representatives of the slum's residents, health-care workers, managers of facilitation offices, and welfare social service centers that are located in slum areas (Interview's guide is attached). The textual material from the interviews was entered into the MAXQDA software and directed content analysis was used to analyze the data.

RESULTS

Data analysis led to the identification of 4 categories (Sociocultural, Situational, Economical, and Physical environment) and 12 subcategories: Sociocultural: lack of awareness, begging culture, low trust in disease control programs, low bottom-up planning, and increasing violence; Situational: decreasing donors' activities and canceling important meetings; Economical: unemployment, decreasing in income, and increasing limitations of many institutions in providing resources; and Physical environment: inadequate space and inappropriate conditions in some houses and alleys for people protection against Corona viruses.

CONCLUSIONS

Slum residents have faced many challenges during the COVID-19 pandemic. These challenges can affect the health of slum and other urban dwellers. Multidisciplinary thinking and actions are needed. Increase awareness and engagement slum residents in control disease programs should be considered.

Predictors of COVID-19 Vaccine Confidence: Findings from Slums of Four Major Metro Cities of India

There are limited studies on COVID vaccine confidence at the household level in urban slums, which are at high risk of COVID-19 transmission due to overcrowding and poor living conditions. The objective was to understand the reasons influencing COVID-19 vaccine confidence, in terms of barriers and enablers faced by communities in urban slums and informal settlements in four major metro cities in India. A mixed method approach was adopted, where in field studies were conducted during April-May 2021. First, a survey of at least 50 subjects was conducted among residents of informal urban settlements who had not taken any dose of the COVID-19 vaccine in Mumbai, Bengaluru, Kolkata and Delhi; second, a short interview with five subjects who had taken at least one dose of the vaccine in each of the four cities to understand the factors that contributed to positive behaviour and, finally, an in-depth interview of at least 3 key informants in each city to ascertain the vaccination pattern in the communities. The reasons were grouped under contextual, individual/group and vaccine/vaccination specific issues. The most frequent reason (27.7%) was the uncertainty of getting the vaccine. The findings show the need for increasing effectiveness of awareness campaigns, accessibility and the convenience of vaccination, especially among vulnerable groups, to increase the uptake.

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.

Habitat vulnerability in slum areas of India - What we learnt from COVID-19?

UN-Habitat identified the present COVID-19 pandemic as 'city-centric'. In India, more than 50% of the total cases were documented in megacities and million-plus cities. The slums of cities are the most vulnerable due to its unhygienic environment and high population density that requires an urgent implementation of public healthcare measures. This study aims to examine habitat vulnerability in slum areas to COVID-19 in India using principal component analysis and Fuzzy AHP based technique to develop slum vulnerability index to COVID-19 (SVI_covid-19). Four slum vulnerability groups (i.e. principal components) were retained with eigen-values greater than 1 based on Kaiser criterion - poor slum household status; lack of social distance maintenance; high concentrations of slum population and towns and mobility of the households. This study also mapped composite SVI_covid-19 on the basis of PCA and Fuzzy AHP method at the state level for a better understanding of spatial variations. The result shows that slums located in the eastern and central parts of India (particularly Uttar Pradesh, Bihar, Jharkhand, Odisha, West Bengal) were more vulnerable to COVID-19 transmission due to lack of availability as well as accessibility to the basic services and amenities to slum dwellers. Thus, the findings of the study may not only help to understand the habitat vulnerability in slum areas to COVID-19 but it will also teach a lesson to implement effective policies for enhancing the quality of slum households (HHs) and to reduce the health risk from any infectious disease in future.

SARS-CoV-2 infection in India bucks the trend: Trained innate immunity?

SARS-CoV-2, the causative agent of COVID-19 pandemic caught the world unawares by its sudden onset in early 2020. Memories of the 1918 Spanish Flu were rekindled raising extreme fear for the virus, but in essence, it was the host and not the virus, which was deciding the outcome of the infection. Age, gender, and preexisting conditions played critical roles in shaping COVID-19 outcome. People of lower socioeconomic strata were disproportionately affected in industrialized countries such as the United States. India, a developing country with more than 1.3 billion population, a large proportion of it being underprivileged and with substandard public health provider infrastructure, feared for the worst outcome given the sheer size and density of its population. Six months into the pandemic, a comparison of COVID-19 morbidity and mortality data between India, the United States, and several European countries, reveal interesting trends. While most developed countries show curves expected for a fast-spreading respiratory virus, India seems to have a slower trajectory. As a consequence, India may have gained on two fronts: the spread of the infection is unusually prolonged, thus leading to a curve that is "naturally flattened"; concomitantly the mortality rate, which is a reflection of the severity of the disease has been relatively low. I hypothesize that trained innate immunity, a new concept in immunology, may be the phenomenon behind this. Biocultural, socioecological, and socioeconomic determinants seem to be influencing the outcome of COVID-19 in different regions/countries of the world.

Agent-Based Computational Epidemiological Modeling

The study of epidemics is useful for not only understanding outbreaks and trying to limit their adverse effects, but also because epidemics are related to social phenomena such as government instability, crime, poverty, and inequality. One approach for studying epidemics is to simulate their spread through populations. In this work, we describe an integrated multi-dimensional approach to epidemic simulation, which encompasses: (1) a theoretical framework for simulation and analysis; (2) synthetic population (digital twin) generation; (3) (social contact) network construction methods from synthetic populations, (4) stylized network construction methods; and (5) simulation of the evolution of a virus or disease through a social network. We describe these aspects and end with a short discussion on simulation results that inform public policy.

COVID-19, poverty and inclusive development

The COVID-19 epidemic provides yet another reason to prioritize inclusive development. Current response strategies of the global community and countries expose a low level of solidarity with poorer nations and poorer people in all nations. Against this background, this paper addresses the question: What are the development challenges that the COVID-19 pandemic lays bare and what lessons can be learnt for the way recovery processes are designed? Using an inclusive development and DPSIR lens to assess the literature, our study finds that, first, the current response prioritises the 'state' and 'impact' concerns of wealthier classes at the expense of the remainder of the world population. Second, responses have ignored underlying 'drivers' and 'pressures', instead aiming at a quick recovery of the economy. Third, a return to business-as-usual using government funding will lead to a vicious cycle of further ecological degradation, socio-economic inequality and domestic abuse that assist in exacerbating the drivers of the pandemic. We argue instead for an inclusive development approach that leads to a virtuous cycle by emphasizing human health, well-being and ecosystem regeneration. We conclude that the lost years for development did not commence in 2020 with the onset of COVID-19; the downward trend has actually been waxing over the past three decades. From this perspective, COVID-19 may be the shock needed to put the last first and transform vicious into virtuous cycles of inclusive development.

Evaluating intervention strategies in controlling coronavirus disease 2019 (COVID-19) spread in care homes: An agent-based model

BACKGROUND

Care homes are vulnerable to widespread transmission of severe acute respiratory coronavirus virus 2 (SARS-CoV-2) with poor outcomes for staff and residents. Infection control interventions in care homes need to not only be effective in containing the spread of coronavirus disease 2019 (COVID-19) but also feasible to implement in this special setting which is both a healthcare institution and a home.

METHODS

We developed an agent-based model that simulates the transmission dynamics of COVID-19 via contacts between individuals, including residents, staff members, and visitors in a care home setting. We explored a representative care home in Scotland in our base case and explore other care home setups in an uncertainty analysis. We evaluated the effectiveness of a range of intervention strategies in controlling the spread of COVID-19.

RESULTS

In the presence of the reference interventions that have been implemented in many care homes, including testing of new admissions, isolation of symptomatic residents, and restricted public visiting, routine testing of staff appears to be the most effective and practical approach. Routine testing of residents is no more effective as a reference strategy while routine testing of both staff and residents only shows a negligible additive effect. Modeling results are very sensitive to transmission probability per contact, but the qualitative finding is robust to varying parameter values in our uncertainty analysis.

CONCLUSIONS

Our model predictions suggest that routine testing should target staff in care homes in conjunction with adherence to strict hand hygiene and using personal protective equipment to reduce risk of transmission per contact.

Prevalence and factors associated with PTSD among female urban slum dwellers in Ibadan, Nigeria: a cross-sectional study

BACKGROUND

Little is known about the prevalence of and factors associated with PTSD among adult females in Nigeria, particularly those who live in slums. PTSD is a mental health condition that develops among some individuals who experience or witness a traumatic event. Several other factors could place individuals at heightened risk of PTSD including stress and comorbid mental disorders. Therefore, this study aimed to examine the prevalence and factors associated with PTSD among female urban slum dwellers in Ibadan, Nigeria.

METHODS

We conducted a cross sectional survey using multistage sampling of 550 women aged 18 and above from selected slums. Interviewer administered questionnaires were used to elicit information on experience of childhood trauma, recent stressors, intimate partner violence, other mental disorders, sociodemographic characteristics and PTSD. PTSD was measured using the Harvard Trauma Questionnaire (HTQ) which is based on DSM IV. A multivariable linear regression model was built to test associations between PTSD and independent variables.

RESULTS

The prevalence for PTSD was found to be 4.18% and the mean PTSD score was 5.80 ± 7.11. Sexual abuse in childhood, past year intimate partner violence and anxiety were significantly associated with higher PTSD scores. PTSD was not significantly associated with a history of recent stressors. Education, employment and marital status were not associated with PTSD however, age and wealth index showed marginal association with PTSD.

CONCLUSION

The prevalence of PTSD among women living in Ibadan slums was relatively low. Both child sexual abuse and intimate partner violence can be prevented. We also recommend longitudinal studies to better understand risk and protective factors.

The effects of non-pharmaceutical interventions on SARS-CoV-2 transmission in different socioeconomic populations in Kuwait: a modeling study

Background

Aggressive non-pharmaceutical interventions (NPIs) may reduce transmission of SARS-CoV-2. The extent to which these interventions are successful in stopping the spread have not been characterized in countries with distinct socioeconomic groups. We compared the effects of a partial lockdown on disease transmission among Kuwaitis (P₁) and non-Kuwaitis (P₂) living in Kuwait.

Methods

We fit a modified metapopulation SEIR transmission model to reported cases stratified by two groups to estimate the impact of a partial lockdown on the effective reproduction number (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ {\mathcal{R}}_e $$\end{document}Re). We estimated the basic reproduction number (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ {\mathcal{R}}_0 $$\end{document}R0) for the transmission in each group and simulated the potential trajectories of an outbreak from the first recorded case of community transmission until 12 days after the partial lockdown. We estimated \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ {\mathcal{R}}_e $$\end{document}Re values of both groups before and after the partial curfew, simulated the effect of these values on the epidemic curves and explored a range of cross-transmission scenarios.

Results

We estimate \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ {\mathcal{R}}_e $$\end{document}Re at 1·08 (95% CI: 1·00–1·26) for P₁ and 2·36 (2·03–2·71) for P₂. On March 22nd, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ {\mathcal{R}}_e $$\end{document}Re for P₁ and P₂ are estimated at 1·19 (1·04–1·34) and 1·75 (1·26–2·11) respectively. After the partial curfew had taken effect, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ {\mathcal{R}}_e $$\end{document}Re for P₁ dropped modestly to 1·05 (0·82–1·26) but almost doubled for P₂ to 2·89 (2·30–3·70). Our simulated epidemic trajectories show that the partial curfew measure greatly reduced and delayed the height of the peak in P₁, yet significantly elevated and hastened the peak in P₂. Modest cross-transmission between P₁ and P₂ greatly elevated the height of the peak in P₁ and brought it forward in time closer to the peak of P₂.

Conclusion

Our results indicate and quantify how the same lockdown intervention can accentuate disease transmission in some subpopulations while potentially controlling it in others. Any such control may further become compromised in the presence of cross-transmission between subpopulations. Future interventions and policies need to be sensitive to socioeconomic and health disparities.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-021-10984-6.

A place-based analysis of COVID-19 risk factors in Bangladesh urban slums: a secondary analysis of World Bank microdata

BACKGROUND

There is a lack of research investigating the confluence of risk factors in urban slums that may make them accelerators for respiratory, droplet infections like COVID-19. Our working hypothesis was that, even within slums, an inverse relationship existed between living density and access to shared or private WASH facilities.

METHODS

In an exploratory, secondary analysis of World Bank, cross-sectional microdata from slums in Bangladesh we investigated the relationship between intra-household population density (crowding) and access to private or shared water sources and toilet facilities.

RESULTS

The analysis showed that most households were single-room dwellings (80.4%). Median crowding ranged from 0.55 m² per person up to 67.7 m² per person. The majority of the dwellings (83.3%), shared both toilet facilities and the source of water, and there was a significant positive relationship between crowding and the use of shared facilities.

CONCLUSION

The findings highlight the practical constraints on implementing, in slums, the conventional COVID19 management approaches of social distancing, regular hand washing, and not sharing spaces. It has implications for the management of future respiratory epidemics.

Policy and research frame of the coronavirus disease 2019 (COVID-19) pandemic: reflections on urban informality

How has the informality of urban slums exposed a gap in policy formulation and research questions in the wake of the coronavirus disease 2019 (COVID-19) pandemic? This paper seeks to identify the appropriate questions and policy frame that would assist future researchers and policymakers on the subject of pandemics in densely populated urban settlements. The authors argue that the nexus between asking the appropriate questions and developing appropriate policy response measures during a pandemic can significantly impact the outcome of the response. The paper examines how the government of Kenya's response to the COVID-19 pandemic reveals a deep-rooted socio-economic and cultural inequality when "blanket" policies are adopted without taking into consideration the unique dynamics characterizing the society. The findings show that the effectiveness of implementing COVID-19 containment policies such as lockdowns, the cession of movement, working from home, distance learning, and social distancing are affected by other factors such as the nature of jobs, one's income levels, where someone lives, cultural beliefs, access to water, sanitation, internet, and medical facilities. This means that a significant number of people within the society experience a double tragedy from the pandemic and impact of government response measures. Yet most of the existing literature has focused on the causes, spread, and impact of the pandemic on health institutions, economies, and public health with little emphasis on the impact on policy measures especially on the vulnerable segments of the society. This paper, therefore, looks at the question of how the various public health intervention strategies disrupt or construct the livelihood of the already complex informal settlement. It provides policymakers and researchers with a number of questions that can frame policy and research during a pandemic with important consideration to urban informality.

Understanding the role of urban design in disease spreading

Cities are complex systems whose characteristics impact the health of people who live in them. Nonetheless, urban determinants of health often vary within spatial scales smaller than the resolution of epidemiological datasets. Thus, as cities expand and their inequalities grow, the development of theoretical frameworks that explain health at the neighbourhood level is becoming increasingly critical. To this end, we developed a methodology that uses census data to introduce urban geography as a leading-order predictor in the spread of influenza-like pathogens. Here, we demonstrate our framework using neighbourhood-level census data for Guadalajara (GDL, Western Mexico). Our simulations show that daily mobility patterns can drive neighbourhood-level variations in the basic reproduction number R 0 , which in turn give rise to robust spatiotemporal patterns in the spread of disease. To generalize our results, we ran simulations in hypothetical cities with the same population, area, schools and businesses as GDL but different land use zoning. Experiments in these synthetic cities demonstrate that the agglomeration of daily activities can influence the growth rate, size and timing of urban epidemics. Overall, these findings support the view that cities can be redesigned to limit the geographical scope of influenza-like outbreaks.

Cohorting to isolate asymptomatic spreaders: An agent-based simulation study on the Mumbai Suburban Railway

The Mumbai Suburban Railways, locals, are a key transit infrastructure of the city and is crucial for resuming normal economic activity. Due to high density during transit, the potential risk of disease transmission is high, and the government has taken a wait and see approach to resume normal operations. To reduce disease transmission, policymakers can enforce reduced crowding and mandate wearing of masks. Cohorting - forming groups of travelers that always travel together, is an additional policy to reduce disease transmission on locals without severe restrictions. Cohorting allows us to: (i) form traveler bubbles, thereby decreasing the number of distinct interactions over time; (ii) potentially quarantine an entire cohort if a single case is detected, making contact tracing more efficient, and (iii) target cohorts for testing and early detection of symptomatic as well as asymptomatic cases. Studying impact of cohorts using compartmental models is challenging because of the ensuing representational complexity. Agent-based models provide a natural way to represent cohorts along with the representation of the cohort members with the larger social network. This paper describes a novel multi-scale agent-based model to study the impact of cohorting strategies on COVID-19 dynamics in Mumbai. We achieve this by modeling the Mumbai urban region using a detailed agent-based model comprising of 12.4 million agents. Individual cohorts and their inter-cohort interactions as they travel on locals are modeled using local mean field approximations. The resulting multi-scale model in conjunction with a detailed disease transmission and intervention simulator is used to assess various cohorting strategies. The results provide a quantitative trade-off between cohort size and its impact on disease dynamics and well being. The results show that cohorts can provide significant benefit in terms of reduced transmission without significantly impacting ridership and or economic & social activity.

The impact of COVID-19 on Venezuelan migrants' access to health: A qualitative study in Colombian and Peruvian cities

This research seeks to understand how COVID-19 has affected access to healthcare among migrants in Latin American cities. Using ethnographic research methods, we engaged with Venezuelans living in conditions of informality in four Colombian cities-Barranquilla, Cucuta, Riohacha, and Soacha-and three Peruvian cities-Lima, Trujillo, and Tumbes. We conducted 130 interviews of both Venezuelan migrants and state and non-governmental actors within the healthcare ecosystems of these cities. We found that forced migrants from Venezuela in both Colombia and Peru face common obstacles along their access trajectories to healthcare, which we summarize as legal, financial, and relating to discrimination and information asymmetry. By limiting effective access to care during the pandemic, these obstacles have also affected migrants' ability to cover the costs of basic needs, particularly food and housing. Our study also found a prevalent reliance on alternative forms of care, such as telemedicine, easy-to-access pharmacies, and extralegal care networks. We conclude that COVID-19 has exacerbated preexisting conditions of informality and health inequities affecting Venezuelan migrants in Colombia and Peru.

Impact of demographic disparities in social distancing and vaccination on influenza epidemics in urban and rural regions of the United States

Background

Self-protective behaviors of social distancing and vaccination uptake vary by demographics and affect the transmission dynamics of influenza in the United States. By incorporating the socio-behavioral differences in social distancing and vaccination uptake into mathematical models of influenza transmission dynamics, we can improve our estimates of epidemic outcomes. In this study we analyze the impact of demographic disparities in social distancing and vaccination on influenza epidemics in urban and rural regions of the United States.

Methods

We conducted a survey of a nationally representative sample of US adults to collect data on their self-protective behaviors, including social distancing and vaccination to protect themselves from influenza infection. We incorporated this data in an agent-based model to simulate the transmission dynamics of influenza in the urban region of Miami Dade county in Florida and the rural region of Montgomery county in Virginia.

Results

We compare epidemic scenarios wherein the social distancing and vaccination behaviors are uniform versus non-uniform across different demographic subpopulations. We infer that a uniform compliance of social distancing and vaccination uptake among different demographic subpopulations underestimates the severity of the epidemic in comparison to differentiated compliance among different demographic subpopulations. This result holds for both urban and rural regions.

Conclusions

By taking into account the behavioral differences in social distancing and vaccination uptake among different demographic subpopulations in analysis of influenza epidemics, we provide improved estimates of epidemic outcomes that can assist in improved public health interventions for prevention and control of influenza.

Electronic supplementary material

The online version of this article (10.1186/s12879-019-3703-2) contains supplementary material, which is available to authorized users.