Epidemiology and Infection Housing, sanitation and living conditions cambridge.org/hyg affecting SARS-CoV-2 prevention interventions in 54 African countries Timothy F. Brewer , Mary Zhang2 , David Gordon2, Roger Yat-Nork Chung3, Original Paper Negussie Dejene4, Cynthia L. Fonta2, Tigist Grieve2, Björn Halleröd5, Cite this article: Brewer TF et al (2021). Housing, sanitation and living conditions Richard Harris2, Alba Lanau6 , Murray Leibbrandt7, Yehualashet Mekonen4, affecting SARS-CoV-2 prevention interventions in 54 African countries. Epidemiology and Bongai Muguni2, Hector Najera8, Shailen Nandy9 and S. Jody Heymann10 Infection 149, e183, 1–6. https://doi.org/ 1 10.1017/S0950268821001734 Department of Medicine, Geffen School of Medicine and Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, USA; 2Bristol Poverty Institute, Townsend Centre for Received: 12 May 2021 International Poverty Research, University of Bristol, Bristol, UK; 3School of Public Health and Primary Care, Revised: 9 July 2021 The Chinese University of Hong Kong, Hong Kong, People’s Republic of China; 4African Child Policy Forum, Addis Accepted: 16 July 2021 Ababa, Ethiopia; 5Department of Sociology and Work Science, University of Gothenburg, Gothenburg, Sweden; 6 Keywords: Centre d’Estudis Demogràfics, Barcelona, Spain; 7African Centre of Excellence for Inequalities Research, COVID-19; non-pharmacologic interventions; University of Cape Town, Cape Town, South Africa; 8Universidad Nacional Autónoma de México, Mexico City, prevention; Africa; public health Mexico; 9School of Social Sciences, Cardiff University, Cardiff, UK and 10Department of Health, Policy & Management, Fielding School of Public Health and Department of Public Policy, Luskin School of Public Affairs, Author for correspondence: University of California, Los Angeles, CA, USA Timothy F. Brewer, E-mail: tbrewer@mednet.ucla.edu Abstract The feasibility of non-pharmacological public health interventions (NPIs) such as physical distancing or isolation at home to prevent severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission in low-resource countries is unknown. Household survey data from 54 African countries were used to investigate the feasibility of SARS-CoV-2 NPIs in low-resource settings. Across the 54 countries, approximately 718 million people lived in households with ⩾6 individuals at home (median percentage of at-risk households 56% (95% confidence interval (CI), 51% to 60%)). Approximately 283 million people lived in households where ⩾3 people slept in a single room (median percentage of at-risk households 15% (95% CI, 13% to 19%)). An estimated 890 million Africans lack on-site water (71% (95% CI, 62% to 80%)), while 700 million people lacked in-home soap/washing facilities (56% (95% CI, 42% to 73%)). The median percentage of people without a refrigerator in the home was 79% (95% CI, 67% to 88%), while 45% (95% CI, 39% to 52%) shared toilet facilities with other households. Individuals in low-resource settings have substantial obstacles to imple- menting NPIs for mitigating SARS-CoV-2 transmission. These populations urgently need to be prioritised for coronavirus disease 2019 vaccination to prevent disease and to contain the global pandemic. Introduction As of 6th July 2021, coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has resulted in approximately 183 million cases and approximately 4 million deaths in more than 200 countries, areas and territories [1], although total mortality due to COVID-19 may be as high as 7 million deaths [2]. The global COVID-19 case fatality ratio approximates that of the 1918 H1N1 Influenza pandemic and regional SARS-CoV-2 outbreaks have overwhelmed the healthcare capacity of high- as well as low- and middle-income countries [3–5]. SARS-CoV-2 spreads primarily by respiratory droplets generated by behaviours such as © The Author(s), 2021. Published by coughing, sneezing or talking, although airborne and fomite transmission also occur [6–8]. Cambridge University Press. This is an Open Until effective vaccines are universally available, non-pharmacological public health interven- Access article, distributed under the terms of tions (NPIs) are the principal means by which governments prevent SARS-CoV-2 transmis- the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), sion in their populations. In addition to isolation of those infected and contact tracing and which permits unrestricted re-use, distribution quarantine for those exposed, the World Health Organization (WHO) recommends physical and reproduction, provided the original article distancing, masking in public places and hand washing as important NPIs that countries is properly cited. should employ for COVID-19 prevention and control [8]. Laboratory-based and observational studies suggest that physical distancing and the wearing of face masks may reduce SARS-CoV-2 transmission by at least 80% [9, 10], and in vitro data demonstrate that alcohol- based hand rubs at WHO recommended concentrations reduce SARS-CoV-2 infectious titres by 3- to 6-fold [11]. These measures, together with shelter-in-place restrictions, have reduced Downloaded from https://www.cambridge.org/core. Universidad Autonoma de Barcelona, on 23 Aug 2021 at 11:45:07, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0950268821001734 2 Timothy F. Brewer et al. SARS-CoV-2 transmission and cases in several countries [12]. Data analyses However, failure to maintain these measures has resulted in resur- The percentage of at-risk people in each country was calculated, gent COVID-19 cases [13, 14]. as was the distribution of at-risk people across all 54 African Persons living in poverty are more likely to suffer severe dis- countries. Summary median at-risk percentages for all 54 coun- ease, require hospitalisation, incur economic hardships or die tries and 95% confidence intervals were determined using the during pandemics, including COVID-19, even in high-income bias-corrected and accelerated bootstrap method. To estimate countries [15]. Given projected shortages of SARS-CoV-2 testing the potential total at-risk population per country, the survey kits in many African countries [16] and delays until vaccines will data were re-weighted by five-year age groups and gender using be widely available, WHO-recommended NPIs are the main the United Nations African country population estimates for COVID-19 prevention tools available to countries facing a resur- 2020 [21]. To assess the effect of survey data on the results, gent pandemic. Many African countries have experienced rapid sensitivity analyses were performed limiting the analyses to the growth in their urban populations living in poverty that may 35 countries (65%) with data from 2015 or later. lack the resources to implement WHO-recommended NPIs Ethics approval was obtained by the institutions that except for mask wearing, if available [17, 18]. Moreover, WHO administered the surveys according to their national require- has documented a recent rapid rise in cases in Africa amidst ments. All analyses used anonymised survey data. the spread of the Delta variant [1]. Using data from representative household surveys in 54 African countries, we examined living conditions that may affect Results individuals’ ability to shelter-in-place, employ physical distancing or have access to soap and water for handwashing. Household survey data were available for all 54 African countries. The individual country sample sizes ranged from 10 079 (Libya)1 to 186 450 (Nigeria). In total, data were available for 3 471 627 Methods individuals (Table 1). Nationally representative household demographic and socio- economic survey or census data were used to create vulnerability Physical distancing feasibility indices regarding individuals’ feasibility to implement COVID-19 In 36 of 54 African countries, 50% or more of the population lived NPIs. For each country, the most recent available national survey in households with ⩾6 people at the time of the most recent data with detailed living conditions information were used. household survey. In eight countries, ⩾70% of the population Multiple Indicator Cluster Survey (MICS) or Demographic and lived in households with six or more people. Across the 54 coun- Health Survey (DHS) data from 2010 to 2020 were available for tries, the median number of households with ⩾6 people present 45 of 54 African countries (83%) [19, 20]. For countries with mul- was 56.4% (95% confidence interval (CI), 51.2% to 59.8%). At tiple surveys during this period, only the most recent survey was the individual country level, large households ranged from a used. For Somalia data were drawn from the 2011 Somliland and low of 14.0% in Mauritius to a high of 86.1% in Senegal (see Northeast Zone MICS4 surveys. Botswanan results were taken Supplemental Table 1 for additional details). from the Botswana Multi-topic Household Survey of 2015– In 41 out of 51 African countries for which data were available, 2016. MICS or DHS data were not available for Eritrea, Libya, 10% or more of the population lived in households where ⩾3 peo- Mauritius and Seychelles. Other representative household survey ple shared a single sleeping room. In 28 of those countries, 15% or and census data from 2010 to 2020 were used to estimate living more of the population lived in such households. The median conditions in these countries. In 4 of 54 countries (7%), Cape number of people living in households with ⩾3 people in a single Verde, Djibouti, Equatorial Guinea and Morocco, the most recent sleeping room was 15.4% (95% CI, 12.5% to 19.4%), ranging at data were between 2000 and 2009 (Table 1). the country level from 1.5% of the population in Mauritius to 85.7% of people in Eritrea. Across the continent, approximately 718.2 million people lived in households with ⩾6 individuals at Variables home while 282.8 million people lived in households with ⩾3 per- Variables were selected to assess the feasibility of physical distan- sons shared a single sleeping room (see Supplemental Table 1 for cing, routine handwashing, isolation or quarantine at home, as additional details). well as whether household conditions place multiple generations at risk. To assess the feasibility of physical distancing, we relied Handwashing feasibility on measures of whether the household was shared by ⩾6 indivi- duals and whether ⩾3 individuals shared a single sleeping room. In 39 out of 54 African countries, ⩾50% of the population did not The feasibility of regular handwashing was assessed by utilising have access to water in their dwelling/plot. However, in 27 coun- measures of whether the household had piped, well or spring tries, this figure rose to ⩾70%. The median number of Africans water within the dwelling or plot and whether the interviewer that lacked access to water within their dwelling/plot was 70.6% observed the presence of soap and washing facilities in the (95% CI, 61.5% to 79.9%), ranging from 0.6% of the population home. The feasibility of isolating or going into quarantine at in Mauritius to 92.9% of the population in Central African home was based on whether the household had a refrigerator Republic (see Supplemental Table 2 for additional details). and/or cooking facilities and whether the household had toilet Forty-three country surveys had data on whether soap and/or facilities in the home or plot not shared with other households. washing facilities were observed in the home. In 25 countries, The risk of intergenerational transmission was assessed by whether people >60 years old lived in households with ⩾3 1 Libya’s sample contains both Gallup World Poll (N = 4018) and Multi-Sector Needs younger individuals. Assessment survey data (N = 6061). Downloaded from https://www.cambridge.org/core. Universidad Autonoma de Barcelona, on 23 Aug 2021 at 11:45:07, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0950268821001734 Epidemiology and Infection 3 Table 1. Household survey data by country, year, type and sample size Table 1. (Continued.) Unweighted Unweighted Country Year Survey sample size Country Year Survey sample size Algeria 2019 MICS6a 151 745 São Tomé and Príncipe 2019 MICS6 13 957 Angola 2016 Standard 73 914 Senegal 2019 Continuous 40 013 DHS-VIIa DHS-VIII Benin 2018 Standard DHS-VII 73 728 Seychellesc 2010 Census 2010 88 945 a Botswana 2016 BMTHS 24 119 Sierra Leone 2019 Standard DHS-VII 71 645 Burkina Faso 2010 Standard DHS-VI 81 522 d Somalia 2011 MICS4 59 381 Burundi 2017 Standard DHS-VII 77 724 South Africa 2016 Standard DHS-VII 37 925 Cape Verde 2005 DHS (IDSR-II) 26 294 South Sudan 2010 MICS4 55 973 Cameroon 2018 Standard DHS-VII 57 624 Sudan 2014 MICS5 97 049 Central African Republic 2019 MICS6 45 797 United Republic of Tanzania 2016 Standard DHS-VI 62 515 Chad 2019 MICS6 112 604 Togo 2017 MICS6 34 988 Comoros 2012 Standard DHS-VI 24 200 Tunisia 2018 MICS6 44 276 Congo 2014 MICS5 53 849 Uganda 2016 Standard DHS-VII 89 202 Côte d’Ivoire 2016 MICS5 56 522 Zambia 2018 Standard DHS-VII 64 302 Djibouti 2006 MICS3 28 014 Zimbabwe 2019 MICS6 44 472 Democratic Republic of the 2017 MICS6 103 422 Total 3 471 627 Congo Notes:. a Egypt 2014 Standard DHS-VI 117 536 MICS = Multiple Indicator Cluster Survey; DHS = Demographic and Health Survey; BMTHS = Botswana Multi-topic Household Survey; EPHS = Eritrea Population and Health Survey; Equatorial Guinea 2000 MICS2 21 136 GWP = Gallup World Poll; MSNA = Multi-Sector Needs Assessment; HBS = Household Budget a Survey. Eritrea 2010 EPHS 133 387 b The estimates for Mauritius were based on the 2017 Household Budget Survey (HBS) and the 2011 Census data. However, the sample size presented in this table, which is 23 781, Eswatini 2014 MICS5 21 024 only includes the number of individuals in the HBS 2017. To avoid confusion, the number of Ethiopia 2016 Standard DHS-VII 73 901 individuals in the Census 2011 is not included in the survey population total. c The estimates for Seychelles are from the 2010 Census except for overcrowding (⩾6 Gabon 2012 Standard DHS-VI 40 654 household members) which are taken from a sample of 1200 households in Q1 of the 2019 Labour Force Survey. d Gambia 2019 Standard DHS-VII 54 240 Somalia MICS4 (2011) data contain the data from Somaliland and Northeast Zone. Ghana 2018 MICS6 61 254 Guinea 2018 Standard DHS-VII 49 120 Guinea-Bissau 2019 MICS6 49 172 ⩾50% of households were observed not to have soap or washing facilities in the home. In 16 countries, this rose to ⩾70% of the Kenya 2014 Standard DHS-VII 151 093 population. Across countries with available data, the median Lesotho 2018 MICS6 35 110 number of people lacking observed soap/washing facilities in Liberia 2019 Standard DHS-VII 41 423 the household was 55.9% (95% CI, 42.3% to 73.4%), ranging at the country level from 2.5% of people in Libya to 93.8% of people a Libya 2018/ GWP & MSNA 10 079 in Liberia. Overall, 889.5 million people in Africa lacked access to 2020 water in their home/plots while 700 million persons were Madagascar 2018 MICS6 82 875 observed to lack soap/washing facilities in their homes (see Malawi 2016 Standard DHS-VII 119 326 Supplemental Table 2 for additional details). Mali 2018 Standard DHS-VII 54 115 Mauritania 2015 MICS5 67 156 Mauritiusb 2017 HBSa 23 781 Isolation and quarantine feasibility Morocco 2004 Standard DHS-IV 62 891 Across Africa, the median number of people per country without Mozambique 2011 Standard DHS-VI 61 842 a refrigerator in the home was 78.7% (95% CI, 66.7% to 88.1%), ranging at the country level from 2.0% of people in Mauritius Namibia 2013 Standard DHS-VI 40 548 to 98.7% of people in Central African Republic. The median num- Niger 2012 Standard DHS-VI 63 776 ber of people that lacked or shared a toilet with other households Nigeria 2018 Standard DHS-VII 186 450 was 45.1% (95% CI, 39.3% to 51.7%) and 60.6% (95% CI, 51.3% to 67.6%) needed to collect or buy firewood for cooking or had no Rwanda 2015 Standard DHS-VII 54 017 at-home cooking facilities (see Supplemental Table 3 for (Continued ) additional details). Downloaded from https://www.cambridge.org/core. Universidad Autonoma de Barcelona, on 23 Aug 2021 at 11:45:07, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0950268821001734 4 Timothy F. Brewer et al. Fig. 1. Proportion of population with resource challenges to implementing WHO recommended non-pharmaceutical interventions against COVID-19 by vulnerability indicator in 54 countries of Africa. Multigenerational families Implementing these measures entails ensuring that individuals are aware of COVID-19 prevention strategies including maintain- In 26 of the 51 countries with available data, 20% or more of the ing physical distancing of at least one metre away from members population lived in households including both persons >60 years of other households, wearing face coverings, avoiding touching old and ⩾3 younger individuals. The percentage of people in their faces or other people (such as by shaking hands) and wash- multigenerational households including persons >60 years old ing their hands with soap/detergent as soon as they return home. ranged from 8.5% in São Tomé and Príncipe to 55.8% in However, these strategies require that people have sufficient space Senegal. Approximately 245.7 million people in Africa live in and resources to comply with these recommendations. multigenerational households that include at least one person The results illustrate the substantial barriers many African >60 years old. The percentages of people vulnerable to households face in keeping safe from SARS-CoV-2 infection COVID-19 by indicator for each country are shown in Fig. 1. because of living conditions that preclude their ability to quaran- tine, isolate or maintain physical distancing and because of sub- Sensitivity analyses stantial obstacles to handwashing. When people need to leave their homes daily to access food, water, cooking or sanitation The analyses were repeated limiting the dataset to the 35 countries facilities, it is difficult (if not impossible) for them to isolate them- with results from 2015 or later. The point estimate for each vari- selves in their homes for extended periods of time to avoid able outcome using this truncated dataset was the same or slightly COVID-19 infections. Physical distancing policies – such as lock- higher than the results for the corresponding variables from the downs – that depend on persons remaining in their homes for overall dataset (Table 2). extended periods of time, are unlikely to be feasible or effective in many low-resource settings even when implemented only for short periods. Discussion Approximately 718.2 million people (about 54% of the African Until vaccines for COVID-19 are widely available in every coun- population) lived in households with ⩾6 individuals at home, try, NPIs are the primary tools for preventing SARS-CoV-2 trans- while 282.8 million people (∼21% of the African population) mission and associated COVID-19 morbidity and mortality. slept in a room with ⩾3 persons. These COVID-19 vulnerability Downloaded from https://www.cambridge.org/core. Universidad Autonoma de Barcelona, on 23 Aug 2021 at 11:45:07, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0950268821001734 Epidemiology and Infection 5 Table 2. Median percentage of African households with potential challenges to implementing non-pharmacologic interventions to prevent COVID-19 54 Countries 2015 or later surveys (35 countries) COVID-19 Metric Median 95% CIa Median 95% CIa ⩾6 persons per household 0.56 0.51–0.60 0.56 0.50–0.59 ⩾3 persons sharing a single sleeping room 0.15 0.13–0.19 0.15 0.12–0.19 Lacking water in dwelling/plot 0.71 0.62–0.80 0.75 0.68–0.84 No observed soap/washing facilities in household 0.56 0.42–0.73 0.62 0.47–0.74 No in-home refrigerator 0.79 0.67–0.88 0.82 0.74–0.90 No toilet in home 0.45 0.39–0.52 0.45 0.33–0.53 No in-home cooking facilities or need for firewood 0.61 0.51–0.68 0.63 0.52–0.70 a Confidence interval. indicator results show that, in many African countries, large num- consequences as COVID-19 cases and deaths rise in middle- and bers of people are unlikely to be able to isolate within their homes, low-income countries [1]. Given the magnitude of obstacles to creating a high-risk for household transmission of SARS-CoV-2. implementing NPIs in countries across Africa, getting sufficient Over 245.7 million individuals (about 18%) live in multigener- vaccine supplies to Africa urgently needs to be prioritised. ational households with at least one person >60 years old, placing SARS-CoV-2 is the latest in a series of respiratory viral outbreaks millions of elderly Africans at risk for COVID-19 infection [22]. to have caused substantial morbidity, mortality and economic dis- Over 889.5 million persons (about 66%) do not have in-home ruption over the last two decades [23, 24]. Other recent respiratory sources of water and 700 million persons (about 52%) lack soap virus outbreaks include the severe acute respiratory syndrome and washing facilities. These conditions preclude routine hand- (SARS) and Middle East respiratory syndrome (MERS) corona- washing, an essential non-pharmacological COVID-19 prevention viruses and the H5N1 and H1N1 influenza viruses. Given the measure. Moreover, additional risks for population-based ongoing risk for respiratory viral epidemics and pandemics, long- COVID-19 spread exist for which data were not available for all term global resource commitments for combatting poverty, improv- countries. These risks include needing to access crowded markets ing housing, water and sanitation, and scaling up vaccine produc- for food and income and the necessary mobility of children, youth tion and ensuring access to vaccines for all people at high risk of and adults outside of the household for education and work. infection, regardless of country of origin, are needed. The use of nationally representative survey data for each coun- In conclusion, hundreds of millions of people across Africa try is a strength of this analysis. Though 35 of the 54 datasets used lack means for implementing NPIs to prevent SARS-CoV-2 trans- (65%) were based on surveys collected since 2015, four surveys mission. These findings raise the urgency of getting vaccines rap- were ⩾10 years old. Many sub-Saharan African countries have idly to all countries in Africa and for addressing the underlying experienced substantial growth in their urban populations living conditions of poverty that place populations at increased risk in poverty during this period [17], and the older surveys may for morbidity and mortality from respiratory virus outbreaks not reflect current population demographics. However, limiting and pandemics. the analyses to the 35 countries with survey data from 2015 or later gave results consistent with the overall dataset with any ten- Supplementary material. The supplementary material for this article can dency towards change being a slight worsening of conditions. be found at https://doi.org/10.1017/S0950268821001734. Although the nationally representative surveys provide important data on living conditions, limitations of this study include the lack Financial support. We acknowledge funding from the UK Research and Innovation Global Challenge Research Fund (GCRF) (Grant Ref: ES/ of information on working and transportation conditions. T010487/1), the Conrad N. Hilton Foundation, the Bill and Melinda Gates Additionally, risk for SARS-CoV-2 infection will be modulated by Foundation, the Elisabeth Blackwell Institute for Health Research and the the relative amount of time susceptible persons spend indoors vs. Beatriu de Pinós fellowship programme. outdoors when exposed to infectious persons. This modifying factor cannot be assessed using these data. The surveys do not include Data. The study data are available from the Multiple Indicator Cluster Survey information regarding non-household and non-resident popula- (MICS), Demographic and Health Survey (DHS), Botswana Multi-topic tions, which may have different risks for COVID-19 infections Household Survey (BMTHS), Eritrea Population and Health Survey (EPHS), compared with household residents. The surveys also do not include Gallup World Poll 2015–2018 Libya microdata aggregated (GWP), Libya Multi-Sector Needs Assessment (MSNA), Mauritius Household Budget information about home ventilation or the length of time household Survey (HBS) and Mauritius 2011 Census data. The availability of the data members spend in their homes, which may be independent is upon registration and used under licences. Links for imputed data from SARS-CoV-2 risk factors. 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