COVID-19 and Slums: A Pandemic Highlights Gaps in Knowledge About Urban Poverty

Community engagement and involvement in managing the COVID-19 pandemic among urban poor in low-and middle-income countries: a systematic scoping review and stakeholders mapping

BACKGROUND

Community engagement and involvement (CEI) was crucial for the COVID-19 pandemic response, particularly among the urban poor in low-and middle-income countries (LMICs). However, no evidence synthesis explores how CEI can benefit public health emergencies.

OBJECTIVE

We conducted a systematic scoping review of the CEI with an emphasis on stakeholder identification, accountability mapping, the support system, and the engagement process among urban poor populations in LMICs during the COVID-19 pandemic.

METHODS

We searched eleven databases, including PubMed, Embase, Web of Science, and CINAHL, following the PRISMA-2020 guidelines to find articles published between November 2019 and August 2021. PROSPERO registration No: CRD42021283599. We performed the quality assessment using a mixed-method appraisal tool. We synthesized the findings using thematic framework analysis.

RESULTS

We identified 6490 records. After the title and abstract screening, 133 studies were selected for full-text review, and finally, we included 30 articles. Many stakeholders were involved in COVID-19 support, particularly for health care, livelihoods, and WASH infrastructure, and their accountability mapping by adopting an interest - influence matrix. This review emphasizes the significance of meaningful CEI in designing and implementing public health efforts for pandemic management among urban slum populations. The interest - influence matrix findings revealed that specific community volunteers, community-based organizations, and civil society organizations had high interest but less influence, indicating that it is necessary to recognize and engage them.

CONCLUSION

Motivation is crucial for those with high influence but less interest, such as corporate responsibility/conscience and private food supply agencies, for the health system's preparedness plan among urban populations.

Towards a Link between Quantitative and Qualitative Sciences to Understand Social Systems Using the Example of Informal Settlements

Urbanization is one of the defining trends of our time and appropriate models are needed to anticipate the changes in cities, which are largely determined by human behavior. In the social sciences, where the task of describing human behavior falls, a distinction is made between quantitative and qualitative approaches, each of which has its own advantages and disadvantages. While the latter often provide descriptions of exemplary processes in order to describe phenomena as holistically as possible, the goal of mathematically motivated modeling is primarily to make a problem tangible. Both approaches are discussed in terms of the temporal evolution of one of the dominant settlement types in the world today: informal settlements. These areas have been modeled in conceptual works as self-organizing entities and in mathematical works as Turing systems. It is shown that the social issues surrounding these areas need to be understood both qualitatively and quantitatively. Inspired by the philosopher C. S. Peirce, a framework is proposed in which the various modeling approaches describing these settlements can be combined to arrive at a more holistic understanding of this phenomenon by using the language of mathematical modeling.

Knowledge, attitude, and practice of Bangladeshi urban slum dwellers towards COVID-19 transmission-prevention: A cross-sectional study

The first COVID-19 case in Bangladesh was detected on March 8, 2020. Since then, efforts are being made across the country to raise awareness among the population for preventing the spread of this virus. We aimed to examine the urban slum dwellers' knowledge, attitude, and practice (KAP) towards COVID-19 transmission-prevention. A phone-based cross-sectional survey was conducted in five slums of Dhaka City. Total 476 adult slum dwellers were interviewed between October 31 to December 1, 2020 using a pre-tested questionnaire. During an interview, information was collected on participants' demographic characteristics and KAP items towards COVID-19. We used quartiles for categorization of knowledge and practice score where the first quartile represents poor, the second and third quartiles represent average while the fourth quartile represents good. Attitude score was standardized using z-score and identified as positive and negative attitude. Multiple linear regression models were used separately to identify the socioeconomic predictors of the KAP scores. The results showed that 25% of the respondents had good knowledge and 25% had poor knowledge, 48% had a positive attitude and 52% had a negative attitude, and 21% maintained good practice and 33% maintained poor practice towards COVID-19 transmission-prevention. About 75% respondents relied on television for COVID-19 related information. Regression results showed that knowledge and attitude scores were significantly higher if respondents had primary or secondary and above level of education compared to the uneducated group. Female respondents maintained significantly good practice compared to their male counterparts (β = 6.841; p<0.01). This study has found that one third of the studied slum dwellers maintained poor practice and one fourth had poor knowledge towards COVID-19 transmission-prevention. As KAP domains are significantly correlated, efforts are needed to raise awareness of COVID-19 particularly targeting individuals with average and lower knowledge to improve attitude and practice for the prevention of COVID-19.

The impact of COVID-19 on the livelihoods of Kenyan slum dwellers and the need for an integrated policy approach

This paper aims to deal with the impact of COVID-19 on the livelihoods of disadvantaged persons living in slums in Kenya. Months after the first case of COVID-19 was reported in Kenya in March 2020, most of the studies that have been carried out pertaining to its impact on slum dwellers have concentrated on narrowly defined concerns e.g. the impact of COVID-19 on youth, gender based violence and nutrition. It is thus difficult to get a clear global picture of the overall impact of COVID-19 on the livelihoods of slum dwellers in Kenya. This paper relies on information gathered during a comprehensive qualitative micro study covering numerous aspects of slum dwellers’ livelihoods, as well as information that has been produced by the Ministry of Health, civil society organizations that work in specific slums, private research organizations as well as local and foreign media houses. The slums whose information is reported in this paper were selected to be indicative of the over 300 slums that are located in Nairobi and Mombasa, the two most important cities in Kenya. The analysis concludes that slum dwellers were potentially at a higher risk under the pressures of COVID-19 of deteriorating conditions with regard to the provision of health services, employment, gender-based violence, education and youth-related problems, and human rights violations, and offers several recommendations to the government.

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.

The Influence of Ethnic, Social, and Demographic Factors on Urban Slum Dwellers' Threat Appraisal, Awareness, and Protective Practices against COVID-19 in Thailand

This study aimed to analyze the influence of ethnicity and other demographic and social factors on urban slum dwellers' threat appraisal, awareness, and protective practices against COVID-19. It was conducted via 20 semi-structured interviews and 453 questionnaires for different ethnic groups from Thailand, Myanmar, Laos, and Cambodia in the slum communities of Khlong Toei, Bangkok-the largest slum in Thailand. A phenomenological approach was used to analyze the semi-structured interviews to understand dwellers' lived experiences and behaviors regarding COVID-19. The questionnaire data were analyzed using descriptive statistics and a multiple regression model. The main findings in this study were that age (elderly people), gender (female), ethnicity (foreign ethnic groups), and type of residential occupancy (living in unoccupied spaces, under tollways, and by railroads) were significant risk factors for vulnerability to COVID-19. Type of residential occupancy and occupation (daily wage workers) were risk factors for severity of COVID-19. Higher education and female gender were factors influencing COVID-19 awareness in all ethnic groups; women tended to practice COVID-19 protection guidelines better than men. Foreign ethnic groups and daily wage workers also performed better in COVID-19 protection practices than other groups. This study appeals for urgent intervention and special assistance from development organizations, the government, and society to ensure slum communities' access to clean water, sanitation, and health care, using dwellers' sociodemographic characteristics and ethnicity to help enhance their threat appraisal capacity and coping strategies with regard to the pandemic.

Which urban communities are susceptible to COVID-19? An empirical study through the lens of community resilience

Background

After the lockdown of Wuhan on January 23, 2020, the government used community-based pandemic prevention and control as the core strategy to fight the pandemic, and explored a set of standardized community pandemic prevention measures that were uniformly implemented throughout the city. One month later, the city announced its first lists of “high-risk” communities and COVID-19-free communities. Under the standardized measures of pandemic prevention and mitigation, why some communities showed a high degree of resilience and effectively avoided escalation, while the situation spun out of control in other communities? This study investigated: 1) key factors that affect the effective response of urban communities to the pandemic, and 2) types of COVID-19 susceptible communities.

Methods

This study employs the crisp-set qualitative comparative analysis method to explore the influencing variables and possible causal condition combination paths that affect community resilience during the pandemic outbreak. Relying on extreme-case approach, 26 high-risk communities and 14 COVID-19 free communities were selected as empirical research subjects from the lists announced by Wuhan government. The community resilience assessment framework that evaluates the communities’ capacity on pandemic prevention and mitigation covers four dimensions, namely spatial resilience, capital resilience, social resilience, and governance resilience, each dimension is measured by one to three variables.

Results

The results of measuring the necessity of 7 single-condition variables found that the consistency index of “whether the physical structure of the community is favorable to virus transmission” reached 0.9, which constitutes a necessary condition for COVID-19 susceptible communities. By analyzing the seven condition configurations with high row coverage and unique coverage in the obtained complex solutions and intermediate solutions, we found that outbreaks are most likely to occur in communities populated by disadvantaged populations. However, if lacking spatial-, capital-, and governance resilience, middle-class and even wealthy communities could also become areas where COVID-19 spreads easily.

Conclusions

Three types of communities namely vulnerable communities, alienated communities, and inefficient communities have lower risk resilience. Spatial resilience, rather than social resilience, constitutes the key influencing factor of COVID-19-susceptible communities, and the dual deficiencies of social resilience and governance resilience are the common features of these communities.

Sociodemographic and environmental health risk factor of COVID-19 in Jakarta, Indonesia: An ecological study

Since December 2019, the COVID-19 pandemic has rapidly emerged on a global scale. Many factors have influenced the spread of COVID-19. This research studies the sociodemographic and environmental health risk factors associated with COVID-19. The study used an ecological study design with subdistricts as its unit of analysis. The total population was 44 subdistricts. Data analysis used correlation and linear regression tests. The study results showed that the average COVID-19 incident rate in Jakarta is 99.8 per 10,000 population. Risk factors for the spread of COVID-19 were associated with population's high level of education (B = 3.094, p value<0.001), population density (B = 0.275, p value = 0.029), and slum area (B = 0.404, p value<0.001). The main risk factor for the spread of COVID-19 in Jakarta is high level of education, which can reflect a higher economic status to the population and a tendency to be more mobile. The government needs to enforce a mobility restriction to lessen the spread of COVID-19.

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 (SVIcovid-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 SVIcovid-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.

COVID-19 impacts on household energy & food security in a Kenyan informal settlement: The need for integrated approaches to the SDGs

This longitudinal study presents the joint effects of a COVID-19 community lockdown on household energy and food security in an informal settlement in Nairobi, Kenya. Randomly administered surveys were completed from December 2019-March 2020 before community lockdown (n = 474) and repeated in April 2020 during lockdown (n = 194). Nearly universal (95%) income decline occurred during the lockdown and led to 88% of households reporting food insecurity. During lockdown, a quarter of households (n = 17) using liquefied petroleum gas (LPG), a cleaner cooking fuel typically available in pre-set quantities (e.g. 6 kg cylinders), switched to polluting cooking fuels (kerosene, wood), which could be purchased in smaller amounts or gathered for free. Household size increases during lockdown also led to participants' altering their cooking fuel, and changing their cooking behaviors and foods consumed. Further, households more likely to switch away from LPG had lower consumption prior to lockdown and had suffered greater income loss, compared with households that continued to use LPG. Thus, inequities in clean cooking fuel access may have been exacerbated by COVID-19 lockdown. These findings demonstrate the complex relationship between household demographics, financial strain, diet and cooking patterns, and present the opportunity for a food-energy nexus approach to address multiple Sustainable Development Goals (SDGs): achieving zero hunger (SDG 2) and universal affordable, modern and clean energy access (SDG 7) by 2030. Ensuring that LPG is affordable, accessible and meets the dietary and cooking needs of families should be a policy priority for helping improve food and energy security among the urban poor.

COVID-19 impacts on household energy & food security in a Kenyan informal settlement: The need for integrated approaches to the SDGs

This longitudinal study presents the joint effects of a COVID-19 community lockdown on household energy and food security in an informal settlement in Nairobi, Kenya. Randomly administered surveys were completed from December 2019-March 2020 before community lockdown (n = 474) and repeated in April 2020 during lockdown (n = 194). Nearly universal (95%) income decline occurred during the lockdown and led to 88% of households reporting food insecurity. During lockdown, a quarter of households (n = 17) using liquefied petroleum gas (LPG), a cleaner cooking fuel typically available in pre-set quantities (e.g. 6 kg cylinders), switched to polluting cooking fuels (kerosene, wood), which could be purchased in smaller amounts or gathered for free. Household size increases during lockdown also led to participants' altering their cooking fuel, and changing their cooking behaviors and foods consumed. Further, households more likely to switch away from LPG had lower consumption prior to lockdown and had suffered greater income loss, compared with households that continued to use LPG. Thus, inequities in clean cooking fuel access may have been exacerbated by COVID-19 lockdown. These findings demonstrate the complex relationship between household demographics, financial strain, diet and cooking patterns, and present the opportunity for a food-energy nexus approach to address multiple Sustainable Development Goals (SDGs): achieving zero hunger (SDG 2) and universal affordable, modern and clean energy access (SDG 7) by 2030. Ensuring that LPG is affordable, accessible and meets the dietary and cooking needs of families should be a policy priority for helping improve food and energy security among the urban poor.

Low-income neighbourhood was a key determinant of severe COVID-19 incidence during the first wave of the epidemic in Paris

BACKGROUND

Previous studies have demonstrated that socioeconomic factors are associated with COVID-19 incidence. In this study, we analysed a broad range of socioeconomic indicators in relation to hospitalised cases in the Paris area.

METHODS

We extracted 303 socioeconomic indicators from French census data for 855 residential units in Paris and assessed their association with COVID-19 hospitalisation risk.

FINDINGS

The indicators most associated with hospitalisation risk were the third decile of population income (OR=9.10, 95% CI 4.98 to 18.39), followed by the primary residence rate (OR=5.87, 95% CI 3.46 to 10.61), rate of active workers in unskilled occupations (OR=5.04, 95% CI 3.03 to 8.85) and rate of women over 15 years old with no diploma (OR=5.04, 95% CI 3.03 to 8.85). Of note, population demographics were considerably less associated with hospitalisation risk. Among these indicators, the rate of women aged between 45 and 59 years (OR=2.17, 95% CI 1.40 to 3.44) exhibited the greatest level of association, whereas population density was not associated. Overall, 86% of COVID-19 hospitalised cases occurred within the 45% most deprived areas.

INTERPRETATION

Studying a broad range of socioeconomic indicators using census data and hospitalisation data as a readily available and large resource can provide real-time indirect information on populations with a high incidence of COVID-19.