Unintended Socio-Economic and Health Consequences of COVID-19 among Slum Dwellers in Kampala, Uganda

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Whereas lockdowns contributed to the control of the pandemic, there were concerns about the unintended consequences of these measures especially in the most vulnerable populations. We assessed unintended socio-economic and health consequences due to the COVID-19 pandemic and the mitigation measures in slums in Kampala to inform the on-going and future pandemic response strategies. Methods This was a mixed methods cross-sectional study conducted in Bwaise I and Bwaise III slums of Kawempe division, Kampala Uganda from October to December 2020. We used systematic sampling to randomly select 425 household heads for the face-to-face quantitative interviews. We also conducted six focus group discussions (FGDs) with slum dwellers and used photovoice among eight Community Health Workers (CHWs) to document unintended socio-economic and health consequences. Quantitative data were imported into STATA version 14.0 for analysis, while qualitative data were analysed thematically using NVivo version 12. Modified Poisson regression analysis was conducted to establish factors associated with impact on access to food. Results Most respondents reported limited access to food (71.1%; 302/425); disruption in education (77.1%; 270/350); drop in daily income and wages (86.1%; 329/382) and loss of employment (63.1; 125/198). Twenty five percent of the respondents (25.4%; 86/338) reported domestic violence as one of the challenges. Seven themes emerged from the qualitative findings on the impact of COVID-19 including: limited access to food; negative impact on children’s rights (child labour and early pregnancies) and education; poor housing and lack of accommodation; negative social behaviours; negative impact on family and child care; reduced income and employment; and negative impact on health and access to health care services. Conclusion The slum dwellers of Bwaise I and Bwaise III experienced several negative socio-economic consequences of COVID-19 and its prevention measures that severely affected their wellbeing. Children experienced severe consequences such as child labour and early pregnancies among the girls. Response activities should be contextualised to different settings and protocols to protect the vulnerable groups in the community such as children and women should be developed and mainstreamed in response activities. Health Policy Photovoice unintended consequences COVID-19 Slum dwellers Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Background Coronavirus disease (COVID-19) has greatly affected the world leading to high morbidity and mortality [ 1 ]. To date (8th September, 2021), there are 212,648,869 confirmed cases of COVID-19 and 4,582,338 deaths globally [ 2 ]. USA, India and Brazil were the most affected countries with over 38 million, 32 million and 20 million cases respectively. Africa has so far recorded over 8 million confirmed cases and 201,576 deaths. South Africa, Morocco and Tunisia were the most affected countries in Africa [ 3 ]. As of 8th September, 2021, Uganda had a cumulative total of 99,701 confirmed cases of COVID-19 and 3031 deaths [ 2 ]. Frequent hand washing with soap or an alcohol based hand rub; use of face masks; maintaining physical distance; covering the mouth and nose when sneezing or coughing; and avoiding touching the mouth, eyes and nose with unwashed hands were the recommended and widely adopted individual prevention measures for COVID-19 globally [ 1 ]. To reduce community spread of COVID-19, several countries, Uganda inclusive, enforced physical distance, and instituted countrywide lockdowns that involved closing schools and international airports, restricted movement of people, and closure of workplaces, among other restrictions [ 4 – 6 ]. All these individual and community prevention measures were effective in reducing the number of COVID-19 infections though they had severe consequences on people’s social, economic, health and psychological wellbeing [ 6 – 8 ]. In Uganda, the first case of COVID-19 was reported on March 21, 2020 [ 5 ]. Restrictions including a total lockdown were instituted on April 1, 2020 with closure of schools, public transport and formal workplaces except those offering essential services. In addition, the public was encouraged to practice hand hygiene, social/physical distancing and use face masks in public spaces [ 5 , 9 ]. However, there are concerns worldwide that most of the interventions have been “top-down” and may not have been appropriate to the local people in different contexts and likely led to negative socio-economic impact on the vulnerable groups in the communities [ 10 , 11 ]. This has led to several unintended consequences and increased vulnerability in different populations [ 10 ]. A body of literature exists on how public health measures negatively impact communities [ 12 , 13 ]. Unintended consequences normally result from poor policy design, unclear policy goals and inappropriate evidence use [ 12 ]. Identifying negative unintended consequences helps in mitigating the effects and planning for prevention of the same. A study on the socio-economic vulnerability to COVID-19 in the Greater Kampala Metropolitan Area in Uganda showed slum dwellers as the most vulnerable group with a low adaptive capacity [ 14 ]. A similar study among urban refugees living in slums in Uganda revealed increased income insecurity, sexual and gender-based violence and anxiety during the lockdown [ 15 ]. The impact of COVID-19 among the local Ugandan slum dwellers is likely to be much more since they had no organised financial benefits from the government or international relief aid compared to the refugees. Slums in Kampala are characterized by overcrowding with many people living together and in close quarters which makes practicing social distancing, a critical prevention strategy in combating COVID-19, problematic. In addition, slums lack access to adequate basic services such as sanitation, water, food and basic health care services which further increases their vulnerability [ 16 , 17 ]. This study assessed unintended socio-economic and health consequences due to the COVID-19 pandemic and the mitigation measures in slums in Kampala to draw lessons to inform the on-going and future pandemic response strategies. Methods Study setting The study was conducted in Bwaise I and Bwaise III slums of Kawempe division, Kampala Uganda from October to December 2020. Bwaise is one of the largest slum areas in Kampala with a mixture of commercial, industrial and residential settlements. Bwaise I slum has a total population of 37,500 and an average household size of 5. Bwaise III has a population of 35,000 people and also an average household size of 5 as well [18]. The two slums are characterised by poor infrastructure and service provision which creates poor housing, flooding and challenges in access to water, sanitation and hygiene [16]. The two slums are located within the Kampala Central business District (CBD) which has a high COVID-19 exposure index [14]. According to a study on the socio-economic vulnerability to COVID-19 in the Greater Kampala Metropolitan Area, Bwaise I and Bwaise III slums had the lowest adaptive capacity. Adaptive capacity in this study was assessed in terms of food security, level of income and access to good health care [14]. The study was conducted in October to December 2020, after the first lockdown was lifted on most activities except a few like bars and sports activities. Study design and population This was a mixed methods cross-sectional study using a sequential explanatory approach. Qualitative data was collected for triangulation and to complement findings from the quantitative study. The study participants included household heads of slum dwellers aged 18 years and above for the quantitative component, and community health workers and purposively selected community members for the qualitative study. In the qualitative study, we used focus group discussions (FGDs) and photovoice. Photovoice is a visual qualitative method used in community-based participatory research to document insights and perspectives which raise awareness of hidden or overlooked issues and aspects of the community [19]. Sample size and sampling procedure A total of 425 respondents were randomly selected for the face-to-face quantitative interviews using systematic sampling. This sample size was calculated using the Kish Leslie (1964) formula for cross sectional studies and the following assumptions were considered; a conservative proportion of 50% had been done at the time of the study, confidence level of 95%, power of 80%, and a non-response rate of 10%. In each zone, we listed all the households with the help of the local chairperson and determined the ‘ k th’ interval, k being the total number of households in the zone divided by the sample size of households needed in that zone. To select a starting point, we stood at the centre of the zone with guidance from the local chairperson and randomly selected the starting household using a table of random numbers. Subsequent households were selected using the “ k th” number. Six FGDs were conducted with purposively selected participants based on those who are more knowledgeable and well versed with community wellbeing such as local leaders and elders. For the photovoice method, we selected eight Community Health Workers (CHWs) as the photographers—four CHWs (two females and two males) were identified in each of the two study areas. The CHWs were identified with the help of other CHWs and the local political leaders in the study areas. Selection of the CHWs was based on their area of jurisdiction, level of education, occupation and marital status to ensure diverse representation and capturing of rich photographs from their areas of influence [20]. Data collection Interviewer administered face-to-face interviews were conducted with household heads using a semi-structured questionnaire in the local language, Luganda, to assess the unintended socio-economic and health consequences due to the COVID-19 pandemic and response activities. Eight research assistants with research experience in quantitative data collection were recruited and trained to do the data collection. The questionnaire was uploaded on the Kobocollect toolbox mobile phone application and mobile phones were used for data collection. In case the kth household selected was closed on the day of data collection or if there was no proxy respondent, we rescheduled the interview for the following day and if on two subsequent times there was no respondent, we considered the next house in the same direction. We also conducted six FGDs in Luganda, the local language, to further assess community socio-economic and health consequences due to COVID-19 and response activities. By the 6 th FGD, there was no more new information arising from the interviews. The FGDs were conducted within 50 minutes to 1 hour with 7-8 participants per session using a guide. Two FGDs included only male participants; two had only female participants while two had both male and female participants. Each FGD was moderated by a researcher experienced in conducting FGDs, key notes taken, and the discussion audio recorded. For photovoice, we used photographs to explore the immediate socio-economic and health consequences due to COVID-19 and response activities. Using a guide , the selected CHWs were trained in data collection using photography. The training covered study objectives, ethics in photography, use and care of cameras, professionalism and obtaining informed consent before taking the photographs. The training on ethics was guided by findings from a study which explored ethical considerations in the work of a CHW [21]. The research team conducted onsite supervision during photography to review the photos to ensure appropriate and clear photos. The CHWs took as many photographs as possible in one month to capture situations in their communities that were related to socio-economic and health consequences arising from the COVID-19 pandemic and response activities. A field guide with pre-determined themes was used to guide the photography. Photographers were however at liberty to take photos related to the study even if they did not fall under any pre-determined theme. Four (4) weekly meetings lasting approximately 3-4 hours were held every Saturday with CHWs and the research team to discuss the photos taken during the previous week. The number of weekly meetings was dependant on theoretical content saturation. In the weekly meetings, each CHW was asked to talk about their photographs and discuss how the pictures related to their lives and those of the community, and how they related to the pre-determined themes of the study. The meetings were moderated by a researcher with experience in using photovoice, and notes of emerging issues taken by a note taker. All discussions for the meetings were audio-recorded. All photos taken in the study were presented back to the CHWs at the end and they were asked to identify themes arising. The CHWs then grouped the photos per theme and selected photos that best represent each theme and their community through consensus. Data management and analysis All study tools were pretested in a similar setting and adjusted accordingly prior to data collection to ensure they yielded the information required. Meetings were also held at the end of each day to check for consistency, completeness, and to ensure proper data collection. The study tool on the phone was fitted with checks to ensure data completeness and accuracy. All data were stored in password protected computers with no personal identifiers. Data from Kobocollect was downloaded from the app into an excel file, cleaned and imported into Stata version 14.0 for further cleaning and analysis. Quantitative data were analysed descriptively generating frequencies and proportions. To measure the association between socio-demographics and limited access to food during the COVID-19 pandemic variable, we ran a modified Poisson regression via generalized linear models to obtain prevalence ratios (PRs). Prevalence ratios were most preferred over odds ratios because the proportion of our outcome variable was >10%, which would have given biased estimates [22]. Variables that had p values of up to 0.2 and those known from literature to be associated with limited access to food during disease outbreaks were included in the multivariable model. All inferential statistics were achieved at 95% confidence interval and 5% alpha level. Audio recordings from the FGDs and photovoice meetings were transcribed verbatim in their original language of recording and translated to English if they were conducted in the local language. Three researchers read through the transcripts several times to familiarise themselves with the data after which they developed a codebook. This was followed with line by line coding by the three independent people. The independent lists of codes from the three researchers were reviewed by two core study team members to assess intercoder agreement. Any discrepancies were clarified and resolved by comparing each coder’s results with raw data until consensus was reached. Coded transcripts were then uploaded into the qualitative analysis software ATLAS.ti Version 7 for thematic analysis using the deductive and inductive approaches. Quotes were then selected to represent the main themes emerging from the study. Ethical considerations We obtained ethical approval from the Makerere University School of Public Health Higher Degrees and Research Ethics Committee (HDREC No.877) and the Uganda National Council of Science and Technology (registration number SS638ES) . Written informed consent was obtained from all study participants before data collection. No photographs identifying an individual were used without the written consent of both the photographer and the identified person. The study team was trained to adhere to the COVID-19 prevention measures during field engagements and constantly supervised for compliance. Results Socio-demographic characteristics of the respondents Out of the 425 respondents for the face-to-face interviews, most were females (66.4%; 282/425); aged 26 to 33 years (26.8%; 114/425); had attained secondary as their highest level of education (46.6%; 198/425); and were Muslims (32%; 136/425). Sixty three percent (268/425) of the respondents reported earning an average of between 50–300,000 Ugandan shillings (less than 100 dollars) per month ( Table 1 ). Table 1 Socio-demographic characteristics of the respondents Variable Frequency (n = 425) Percentage (%) Sex Male 143 33.65 Female 282 66.35 Age (years) 18 to 25 78 18.35 26 to 33 114 26.82 34 to 41 96 22.59 42 to 49 65 15.29 ≥ 50 72 16.94 Mean (SD) 37.22 ± 12.6 Highest level of education No formal education 42 9.88 Primary 155 36.47 Secondary 198 46.59 Tertiary 30 7.06 Marital status Married 166 39.06 Single 94 22.12 Co-habiting 76 17.88 Divorced / separated 59 13.88 Widowed 30 7.06 Religion Anglican 131 30.82 Catholic 99 23.29 Muslim 136 32 Seventh Day Adventist 8 1.88 Pentecostal 41 9.65 Others 10 2.35 Occupation Casual labourer 46 10.82 Employed 44 10.35 Self-employed 221 52 None 113 26.59 Others 1 0.24 Average income earned per month (Ugandan shilling) 50–300,000/= 268 63.06 300,001- 500,000/= 41 9.65 500,001–1,000,000/= 2 0.47 None 114 26.82 Socio-economic And Health Impact Most respondents reported: limited access to food (71.1%; 302/425); disruption in education (77.1%; 270/350); a drop in daily income and wages (86.1%; 329/382); loss of employment, (63.1; 125/198); limited access to cooking energy (52.7%; 224/425); and limited access to transport (68.5%; 291/425). Most respondents mentioned no impact of COVID-19 on: access to water (65.9%; 280/425); sanitation and hygiene facilities (68.7%; 292/425); and access to health care services (71.5%; 304/425). Twenty five percent of the respondents 25.4%; 86/338) reported domestic violence. Almost half (40.2%; 171/425) of the respondents reported mental health challenges including reduced sleep, anxiety and urge to drug use (Table 2 ) . Table 2 Immediate socio-economic and health consequences due to COVID-19 in Bwaise I and Bwaise III, Kampala Uganda Impact on: High Moderate Low No impact Household access to food 302 (71.06) 41 (9.65) 20 (4.71) 62 (14.59) Household access to water 96 (22.59) 28 (6.59) 21 (4.94) 280 (65.88) Household access to sanitation and hygiene services 82 (19.29) 31 (7.29) 20 (4.71) 292 (68.71) Education (n = 350) 270 (77.14) 9 (2.57) 4 (1.14) 67 (19.14) Household daily wages and incomes (n = 382) 329 (86.13) 21 (5.50) 4 (1.05) 28 (7.33) Employment (n = 198) 125 (63.13) 10 (5.05) 8 (4.04) 55 (27.78) Domestic violence (n = 338) 86 (25.44) 22 (6.51) 21 (6.21) 209 (61.83) Social behaviours 40 (9.41) 8 (1.88) 7 (1.65) 370 (87.06) Family welfare 118 (27.76) 30 (7.06) 25 (5.88) 252 (59.29) Household lighting 136 (32.00) 32 (7.53) 26 (6.12) 231 (54.35) Household cooking energy 224 (52.71) 34 (8.0) 17 (4.00) 150 (35.29) Transport 291 (68.47) 22 (5.18) 22 (5.18) 90 (21.18) Health 87 (20.47) 43 (10.12) 17 (4.00) 278 (65.41) Access to health care 89 (20.94) 19 (4.47) 13 (3.06) 304 (71.53) Mental health 171 (40.24) 27 (6.35) 23 (5.41) 204 (48.00) From the analysis of FGDs and photovoice findings, the following themes emerged under socio-economic and health consequences due to COVID-19 and response activities; limited access to food; negative impact on children rights and education; poor housing and lack of accommodation; negative social behaviours; negative impact on family and child care; reduced income and employment; and negative impact on health and access to health care services. Factors associated with one of the highest reported impact on socio-economic and health vulnerabilities due to COVID-19 in Bwaise I and Bwaise III, in Kampala Uganda Impact On Household Access To Food After adjusting for potential confounders, respondents aged 25 to 33 years (adjusted PR = 1.19, 95% CI: 1.01–1.41); 42 to 49 years (adjusted PR = 1.22, 95% CI: 1.01–1.47); and ≥ 50 (adjusted PR = 1.22, 95% CI: 1.01–1.48) were more likely to have limited access to food. Respondents who reported earning an average monthly income of 300,001/= and above were 0.74 times less likely to have limited access to food (adjusted PR = 0.74, 95% CI: 0.55–0.98), see Table 3 . Table 3 Crude and adjusted factors associated with the impact of COVID-19 on household access to food and socio-demographic characteristics Attributes Impact of COVID-19 on household access to food Unadjusted PR (95% CI) Adjusted PR (95% CI) P value Low (n = 82) High (n = 343) P value Sex Male 29 (20.3) 114 (79.7) 0.98 (0.89–1.09) 1.03 (0.93–1.15) 0.542 Female 53 (18.8) 229 (81.2) 1 1 Age (years) 18 to 25 23 (29.5) 55 (70.5) 1 1 26 to 33 19 (16.7) 95 (83.3) 1.18 (1.01–1.39) * 1.19 (1.01–1.41) 0.044 34 to 41 17 (17.7) 79 (82.3) 1.16 (0.98–1.38) 1.18 (0.99–1.41) 0.063 42 to 49 10 (15.4) 55 (84.6) 1.20 (1.01–1.43) * 1.22 (1.01–1.47) 0.038 ≥ 50 13 (18.1) 59 (81.9) 1.16 (0.97–1.39) 1.22 (1.01–1.48) 0.037 Highest level of education No formal education 7 (16.7) 35 (83.3) 1 1 Primary 20 (12.9) 135 (87.1) 1.05 (0.90–1.21) 1.05 (0.91–1.21) 0.496 Secondary 45 (22.7) 153 (77.3) 0.93 (0.79–1.08) 0.96 (0.82–1.12) 0.596 Tertiary 10 (33.3) 20 (66.7) 0.80 (0.60–1.07) 0.84 (0.61–1.15) 0.270 Marital status Married 42 (17.4) 200 (82.6) 1 1 Single 22 (23.4) 72 (76.6) 0.93 (0.82–1.05) 0.99 (0.87–1.12) 0.868 Divorced / separated 12 (20.3) 47 (79.7) 0.96 (0.84–1.11) 0.93 (0.81–1.07) 0.496 Widowed 6 (20.0) 24 (80.0) 0.97 (0.80–1.17) 0.89 (0.74–1.07) 0.225 Occupation before pandemic Casual labourer 7 (15.2) 39 (84.8) 1 1 Employed 13 (29.6) 31 (70.4) 0.83 (0.66–1.04) 0.88 (0.70–1.11) 0.277 Self-employed 44 (19.8) 178 (80.2) 0.95 (0.82–1.09) 0.97 (0.84–1.12) 0.700 None 18 (15.9) 95 (84.1) 0.99 (0.86–1.15) 0.88 (0.72–1.08) 0.225 Average monthly income None 16 (14.0) 98 (86.0) 1 1 50–300,000/= 53 (19.8) 215 (80.2) 0.93 (0.85–1.03) 0.84 (0.69–1.01) 0.060 300,001- above 13 (30.2) 30 (69.8) 0.81 (0.66–1.00) 0.74 (0.55–0.98) 0.035 Unintended immediate social consequences due to COVID-19 and response activities Negative Impact On Children Rights And Education Closure of schools due to COVID-19 with no clear mechanism of continued learning at home exposed most children to several consequences. Photovoice participants noted that some children were exposed to forced labour either to provide extra income to the family or as their own initiative. Engagement of children in labour was mentioned by participants as likely to expose them to COVID-19, sexual violence, early pregnancies, undesirable behaviours and increase school dropout. A photographer explained the extent of the impact on children rights and education. “Many children have become involved in petty trade and most of these are unwilling to return to school. I am sure a substantial percentage of these children will drop out of school when schools fully reopen. Sending children especially girls to sell merchandise is problematic because they may get molested or sexually assaulted by the men they find along the way” (Photographer 3, female, age 38) Participants in both the FGDs and photovoice mentioned increased teenage pregnancies and early child marriages since the onset of COVID-19 (Photo 1). This was attributed to teenage girls being out of school and redundant at home with their parents and guardians focused on making income for survival. Unwanted pregnancies were also attributed to the girls lacking basic needs hence looking out to men for survival. “My issue is that since schools were closed during COVID-19 outbreak, we saw many girls drop out of school. These girls have got unwanted pregnancies and as a mother, I can’t take care of the pregnant girl and the unborn baby because I have no money or a job. I could have taken care of the pregnant girl but the workplaces were closed. We have been affected so much by this situation.” (Female FGD, Participant 2, Bwaise III) Limited access to food Many study participants in the FGDs and photovoice mentioned reduced access to food given that most had their income reduced, lost jobs and some had their businesses shut down during the pandemic. Reduced access to food was expressed in terms of no money to buy the food, increased food prices and limited availability of certain foods. Patients suffering from chronic illnesses were affected more because they had to take their medication on an empty stomach. Most participants mentioned reduced: frequency of meals, eating of a balanced diet and portions (Photo 2) as a coping strategy. “…COVID-19 affected me so much because I was used to eating two meals a day but I can no longer do that. We now have one meal a day and that is supper. We take a cup of tea a day at 4pm and prepare the little food we have. At 7pm, we have our supper and sleep. The earnings also reduced.” (Female FGD, Participant 8, Bwaise III) Impact on family and child care Cases of domestic violence in the slum communities were mentioned to have increased during the COVID-19 pandemic. Participants attributed this to no money to sustain homes, increased leisure time at home and loss of jobs by the bread winners. Relatedly, some families were said to have broken up due to the heightened violence and also increased demands for basic needs from the family. “… I might even shed a tear while talking. First of all, i was beaten up during that time (lockdown). I was beaten up because I had no money. The child would ask me for food but I had nothing. My husband would ask for food and later beat me up. There is nothing I gained from the situation except being beaten up.” (Female FGD, Participant 4, Bwaise III) Increased Drug Use And Abuse Study participants in the photovoice also noted an increase in the number of people using drugs since the beginning of the lockdown (Photo 3). Most people are cited drinking alcohol from early morning hours to evening and others smoking cannabis and marijuana, with some developing mental illnesses. Some photovoice participants attributed the increase in drug use to increased stress in the population due to loss of jobs and income and others attributed it to several people having too much time and idleness, most of them having lost jobs and businesses. “…the truth is we have had a rising number of such cases (cases of drug abusers) due to COVID-19 situation. Because, they (community members) searched for what to do and failed to get a job. They looked for money and what to eat and failed to get so they got frustrated and started drugs. That was a sensible person (photo 5) before COVID-19 situation but now, see what he has become.” (Photographer 7, male, age 32) Unintended Immediate Economic Consequences Due To Covid-19 Reduced income and loss of employment Most participants in photovoice and FGD mentioned loss of employment as one of the consequences of COVID-19. The loss of employment was largely a result of most companies laying off staff and others because of the shutdown of businesses during the lockdown. Loss of employment was said to have greatly impacted access to basic needs and family stability. “…people lost jobs, curfew also affected food sellers because customers were limited, those with bars sent away many workers who are now jobless; those who have lodges aren’t functional yet it also employed many people; boda-boda riders were affected by curfew as well, schools were also affected so much.” (Male FGD, Participant 1, Bwaise III) During the lockdown and after, several businesses in the community collapsed and others had reduced performance in terms of customers and income generation. Collapse of businesses was attributed to some people using up the capital for food to survive during the lockdown and reduced performance attributed to most people having no money to buy from the business vendors. “COVID-19 situation affected me so much because I used to have a retail shop and the school going students would buy from me. I am a widow with many children but I had to close the shop. The little capital I had was used to buy and stock food during the COVID-19 lock down and every day would just pass by. I even lacked money to buy water and sugar.” (Mixed FGD, Participant 6, Bwaise III) Inability To Afford Housing And Accommodation Both photovoice and FGD participants mentioned several community members have since the start of COVID-19 accumulated rent arrears with some being evicted from the houses and shops (Photo 4). Accumulated rent arrears came because of unemployment and reduced income during the lockdown. Some community members were said to have resorted to residing in animal houses offered by neighbours. “This photo shows the effect of COVID-19 on housing. The property in the photo belonged to a tenant who had been evicted. The tenant had rent arrears of four months and the landlord could not tolerate him any longer. Therefore, COVID has left many people homeless.” (Photographer 4, male, age 64) Unintended Immediate Health Consequences Due To Covid-19 Reduced health and limited to access health care services Due to limited movements during the lockdown, increased transport fares and no income, some slum dwellers resorted to not seeking health care when sick. They stayed indoors hoping to get better (Photo 5). More so, most said they were ignored and did not receive care when they visited the health centers as all attention was on COVID-19 patients. Those on chronic medication like people living with HIV, could not refill their medicines because of transport challenges. “Some people who had chronic illnesses such as diabetes, HIV/AIDS and hypertension either worsened or died because there was very limited access to routine healthcare services. The limited access to health care services was due to absence of transport means to health facilities and change in priority of healthcare services to mainly focus on COVID-19 patients and neglecting other diseases.” (Photographer 5, female, age 60) Respondents in the FGDs reported increased mental health conditions because of COVID-19 restrictions and related challenges. Most mentioned increased stress as a result of many needs against no money; others mentioned increased anxiety and disrupted sleep. “We have all lost our minds during this situation. You find people walking while talking to themselves on the street. Others have tried sleeping but failed and others have got accidents because they walk without thinking. The landlords evict us and when you explain to them they also claim they built houses to make money. The children ask for food and when you talk to your husband, he just walks away. What I think is that the mental health issues will worsen in future because of this situation. People will only think 50% because of this stress.” (Female FGD, Participant 8, Bwaise III) Discussion This study assessed the unintended socio-economic and health consequences due to COVID-19 and the response activities. Most respondents reported limited access to access to food, education, daily income and wages and employment, housing, mental health challenges, and increased domestic violence. Other challenges included effects on children rights and education. The unintended consequences due to COVID-19 reported in this study include critical determinants of health and pose a major threat to the wellbeing and health of these communities and could also increase their vulnerability to COVID-19. Our findings revealed challenges in access to food both in terms of physical and financial access. Most respondents accessed only one meal a day, reduced portions or were not able to have a balanced diet. Slum dwellers largely depend on daily wages for food and other essential requirements [ 23 , 24 ]. The prolonged lockdown without socioeconomic support therefore exposed them to severe challenges related to access to food. Uganda integrated food distribution for vulnerable urban populations to reduce the likely impact but this was not adequate in quantities and could not be sustained long enough to avert the challenges with access to food [ 15 ]. Our findings are similar to findings in other studies in Uganda and elsewhere where food security outcomes were worse among poor households which depend on labour income [ 25 , 26 ]. Limited access to food could lead to reduced nutrient intake consequently leading to diet-related and nutrition-related diseases [ 27 ]. Nutrition-related diseases are often associated with reduced immunity which will likely expose more people to COVID-19 and other infections [ 28 ]. The negative impact on children’s rights and education were raised among the challenges. COVID-19 related restrictions led to disruption of education which is likely to have long lasting impact on the children including school dropout, early pregnancies and early marriages for girls, with some unable to go back to school due to lack of school fees. Returning to school after giving birth is not guaranteed because of the stigma that could arise but also increased responsibility to take care of the child [ 29 , 30 ]. In northern and eastern Uganda, an increase in cases of young girls forced to sell sex in return for cash, food, or even sanitary products during the COVID-19 pandemic was reported [ 31 ]. In the Ebola outbreak in West Africa, similar consequences were observed such as teenage pregnancies, school drop outs and early marriages for school going children [ 32 , 33 ]. Children are vulnerable to social and health effects hence there is need to protect them from things that threaten their well being [ 34 – 37 ]. A reduction in daily income, wages and employment was reported. Due to the lockdown, most businesses and formal workplaces were unable to operate leading to no income generation and downsizing. Studies elsewhere have reported financial insecurity, loss of employment and reduced income due to Covid related lockdowns [ 8 , 15 , 31 , 38 – 40 ]. Reduced income affects health care seeking, limited access to basic needs like food and water and increased crime rate [ 41 , 42 ]. In desperation and the pursuit of income for survival, people are likely to engage in risky activities like congregating in large numbers and shunning of the recommended prevention guidelines which may lead to their exposure to COVID-19 [ 43 ]. Therefore, the economic and financial wellbeing of vulnerable populations should be catered for as part and parcel of the pandemic response strategies. Domestic violence was reported to have increased during the COVID-19 pandemic. Increased domestic violence could have been as a result of increased financial stress in families, increased time of closed stay and unfulfilled expectations from partners. Studies elsewhere reported some people losing their lives as a result of the domestic violence, and some sustaining bruises from beatings during the COVID-19 pandemic [ 31 , 44 , 45 ]. In Peru, calls of domestic violence on women to the national helpline increased by 56 percent in April 2020 [ 45 ]. In northern and eastern Uganda, there was an increase in cases of young girls forced to sell sex in return for cash, food, and sanitary products [ 31 ]. Relatedly, the Ebola outbreak in West Africa also resulted in increased cases of gender based violence among teenage girls and young women [ 33 ]. Increased domestic violence threatens the wellbeing of society and family. Our qualitative findings revealed limited access to health care services and worsening of some health conditions. This was reported among persons with chronic illnesses like HIV/AIDS, diabetes, hypertension and others. Studies in other countries have reported reduced health care utilisation and disrupted health care services [ 46 – 49 ]. Reduced health care seeking may lead to poor health outcomes for other diseases and increased risk for community spread of COVID-19 and other infectious diseases due to cases not reporting to the health facilities. Strategies to strengthen and sustain other health services during pandemics such as COVID-19 are essential in ensuring good health outcomes across the board. Mental health challenges were also prominent in this community. Increased mental health challenges such as anxiety, disruption in sleep patterns, stress and so forth may have resulted from forced stay at home during the lockdown, separation from loved ones, restricted movements, uncertainty, boredom and fear of infection. Mental health challenges especially psychological effects have been reported elsewhere [ 15 , 48 , 50 – 53 ]. Disease pandemics are inherently stressful hence adding other stressors such as restriction in movements, work and separation from loved ones worsen the situation, and could have longer term effects after the pandemic. Mental health challenges could also arise from the stigma that is meted on the survivors of infectious disease such as COVID-19 and their families. However, mental health is not always prioritised in disease response strategies. Pandemic response strategies should therefore integrate psychosocial and mental health interventions. A strength to our study is the use of mixed methods to triangulate the unintended socioeconomic and health consequences due to COVID-19 in this vulnerable population. We used the photovoice method which enables community participation in the process and raises awareness of hidden or overlooked issues in the community. Our study however did not establish the baseline status to objectively demonstrate the changes due to COVID-19 and relied on self-reported impact. Further studies are recommended to establish the extent of impact and mitigation interventions. Conclusion The negative consequences of COVID-19 and related restrictions were quite severe among the vulnerable slum dwellers in Kampala. Most respondents reported a high impact on access to food, education, daily income and wages, employment, and access to cooking energy. Domestic violence and mental health as well as effects on child education and rights were also prominent. These findings emphasize the need for comprehensive preparedness and response strategies and plans that cater for the socioeconomic needs especially for the most vulnerable populations. During design of response and prevention activities for disease outbreaks, protocols should be established and mainstreamed to protect vulnerable groups in the community especially children and women. The impact on education and the young school going children could be long-term and requires both immediate and long-term mitigation strategies to ensure continuity of education and minimize future socioeconomic challenges. Abbreviations CBD Central Business District CHWs Community Health Workers COVID-19 Coronavirus Disease FGDs Focus Group Discussions HCD Human-centred design HDREC Higher Degrees Research and Ethics Committee HIV Human Immunodeficiency Virus IRB Institutional Review Board KCCA Kampala Capital City Authority KIIs Key Informant Interviews KIs Key informants NGOs Non- Government Organisations SDG Sustainable Development Goal SOPs Standard Operating Procedures USA United States of America WHO World Health Organisation Declarations Ethics approval and consent to participate We obtained ethical approval to conduct the study from the Institutional Review Board of Makerere University School of Public Health (HDREC No.877) and registered the study with the Uganda National Council of Science and Technology (registration number SS638ES) . Written informed consent was obtained from all study participants using a consent form before any data collection. Participation in the study was voluntary and participants were informed of the study procedures including the use of photographs. No photographs identifying an individual were used without the written consent of both the photographer and the identified person. All methods were carried out in accordance with guidelines and regulations from Makerere University School of Public Health and Uganda National Council of Science and Technology. Consent for publication All authors consented to publishing this manuscript. Study participants also consented to have their information and photographs anonymously published to the wider scientific community. Availability of data and materials Data and materials supporting findings in this manuscript are available upon reasonable request through the Institutional Review Board of Makerere University School of Public Health. They can be contacted at [email protected] . Competing interests The authors declare that they have no competing interests. Funding This work was supported by the Alliance for Health Policy and Systems Research, World Health Organization. The Alliance is supported through both core funding as well as project specific designated funds. The full list of Alliance donors is available here: https://www. who.int/alliance-hpsr/partners/en/. This work also received funding support from the Doris Duke Charitable Foundation. Authors' contributions RN conceptualised the study and spearheaded the implementation of the study including manuscript writing. MN, JBB and SN participated in study implementation, data analysis and manuscript writing. DM and DO gave technical support of the study and manuscript writing. RW gave the overall technical oversight of the study and guided interpretation of study findings. All authors read and approved the manuscript. Acknowledgements We acknowledge the contribution of research assistants who collected the data and the study participants who graciously responded to our questionnaires. We also acknowledge the support from the Alliance for Health Policy and Systems Research, World Health Organization and Kampala Capital City Authority during the study period. Disclaimer: The authors are themselves alone responsible for the views expressed in the Article. This article does not represent the views, decisions, or policies of the Alliance for Health Policy and Systems Research. References WHO. WHO announces COVID-19 outbreak a pandemic 2020 [updated 2020-03-12. WHO. WHO Coronavirus (COVID-19) Dashboard: WHO; 2021 [updated 2:39pm CEST, 27 May 2021; cited 2021 25th August 2021]. Available from: https://covid19.who.int/. Worldometer. Coronavirus Cases. 2021. WHO. Report of the WHO-China Joint Mission on Coronavirus Disease 2019 (COVID-19). WHO, 2020 2020. Report No. MOH. 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Report No. Martin A, Markhvida M, Hallegatte S, Walsh B. Socio-Economic Impacts of COVID-19 on Household Consumption and Poverty. Economics of Disasters and Climate Change. 2020:1-27. Peters DH, Garg A, Bloom G, Walker DG, Brieger WR, Hafizur Rahman M. Poverty and access to health care in developing countries. Annals of the New York Academy of Sciences. 2008;1136(1):161-71. Bengle R, Sinnett S, Johnson T, Johnson MA, Brown A, Lee JS. Food insecurity is associated with cost-related medication non-adherence in community-dwelling, low-income older adults in Georgia. Journal of Nutrition for the Elderly. 2010;29(2):170-91. Taylor S. The psychology of pandemics: Preparing for the next global outbreak of infectious disease: Cambridge Scholars Publishing; 2019. Ravindran S, Shah M. Unintended consequences of lockdowns: Covid-19 and the shadow pandemic. National Bureau of Economic Research, 2020 0898-2937. Agüero JM. Covid-19 and the rise of intimate partner violence. 2020. Pellegrini M, Ponzo V, Rosato R, Scumaci E, Goitre I, Benso A, et al. Changes in Weight and Nutritional Habits in Adults with Obesity during the “Lockdown” Period Caused by the COVID-19 Virus Emergency. Nutrients. 2020;12(7):2016. Ghosal S, Sinha B, Majumder M, Misra A. Estimation of effects of nationwide lockdown for containing coronavirus infection on worsening of glycosylated haemoglobin and increase in diabetes-related complications: a simulation model using multivariate regression analysis. Diabetes & Metabolic Syndrome: Clinical Research & Reviews. 2020. Bodrud-Doza M, Shammi M, Bahlman L, Islam ARMT, Rahman MM. Psychosocial and Socio-Economic Crisis in Bangladesh Due to COVID-19 Pandemic: A Perception-Based Assessment. Frontiers in public health. 2020;8(341). WHO. COVID-19 significantly impacts health services for noncommunicable diseases 2020 [updated 2020. Duan L, Zhu G. Psychological interventions for people affected by the COVID-19 epidemic. The Lancet Psychiatry. 2020;7(4):300-2. Dubey S, Biswas P, Ghosh R, Chatterjee S, Dubey MJ, Chatterjee S, et al. Psychosocial impact of COVID-19. Diabetes & Metabolic Syndrome: Clinical Research & Reviews. 2020. Cellini N, Canale N, Mioni G, Costa S. Changes in sleep pattern, sense of time and digital media use during COVID‐19 lockdown in Italy. Journal of Sleep Research. 2020:e13074. Javed B, Sarwer A, Soto EB, Mashwani ZU. The coronavirus (COVID-19) pandemic's impact on mental health. The International journal of health planning and management. 2020;35(5):993-6. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 13 Jan, 2022 Read the published version in BMC Public Health → Version 1 posted Editorial decision: Major revision 26 Oct, 2021 Reviews received at journal 23 Oct, 2021 Reviews received at journal 22 Sep, 2021 Reviewers agreed at journal 21 Sep, 2021 Reviewers agreed at journal 19 Sep, 2021 Reviewers invited by journal 19 Sep, 2021 Editor assigned by journal 19 Sep, 2021 Editor invited by journal 16 Sep, 2021 Submission checks completed at journal 16 Sep, 2021 First submitted to journal 09 Sep, 2021 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-891320","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":52457837,"identity":"d616faf5-ed7b-4c17-8d20-8e58075a33d8","order_by":0,"name":"Rebecca Nuwematsiko","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/UlEQVRIie3PsUrEQBCA4VkW1kax3RAhr7CHkHAcJq+SZcFrYu2BoAHhbHLYnuhDHAgD1wkDZ+MDBLQQfIGzuyCCu1jK4qUT2b8YpvkYBiAU+tNxAbB2i9wSSEfYvB8BAXx3G5LdNql8r/Lz5Erot6OKiiyu2XoDlNcecvDylEY3aKQiQYcnSHp598CjBsj4iJRV+ryHXCq+M40tKVVbQgyWeH9w5BMvZHJpyRCpsIR//EoYkgQSq9gubNGWwl3J/eT4tJvhY7QgYQYzHOvlXE+HjRqXfmLuVYdn+8n1avDa4ajIpKF2MxkVPvIzBax2U9c9yHc9roRCodA/7wuLF1G2xyauIwAAAABJRU5ErkJggg==","orcid":"","institution":"Makerere University College of Health Sciences","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Rebecca","middleName":"","lastName":"Nuwematsiko","suffix":""},{"id":52457838,"identity":"58f86efb-98f6-447c-a43c-6bc89844b926","order_by":1,"name":"Maxencia Nabiryo","email":"","orcid":"","institution":"Makerere University College of Health Sciences","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Maxencia","middleName":"","lastName":"Nabiryo","suffix":""},{"id":52457839,"identity":"b3554456-a533-4477-9b7a-f35afaa350f2","order_by":2,"name":"John Bosco Bomboka","email":"","orcid":"","institution":"Makerere University College of Health Sciences","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"John","middleName":"Bosco","lastName":"Bomboka","suffix":""},{"id":52457840,"identity":"eb96584b-c4fa-4716-9e84-778d1a8ec518","order_by":3,"name":"Sarah Nalinya","email":"","orcid":"","institution":"Makerere University College of Health Sciences","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Sarah","middleName":"","lastName":"Nalinya","suffix":""},{"id":52457841,"identity":"f1329c28-485c-41bb-8d0c-37f3b6a106a3","order_by":4,"name":"David Musoke","email":"","orcid":"","institution":"Makerere University College of Health Sciences","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"David","middleName":"","lastName":"Musoke","suffix":""},{"id":52457842,"identity":"fe2f8970-5cc8-46df-ada4-075d35d51592","order_by":5,"name":"Daniel Okello","email":"","orcid":"","institution":"Kampala Capital City Authority","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Daniel","middleName":"","lastName":"Okello","suffix":""},{"id":52457843,"identity":"51bd76ab-2f27-4317-9cac-6a684c5028c8","order_by":6,"name":"Rhoda K. 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To date (8th September, 2021), there are 212,648,869 confirmed cases of COVID-19 and 4,582,338 deaths globally [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. USA, India and Brazil were the most affected countries with over 38\u0026nbsp;million, 32\u0026nbsp;million and 20\u0026nbsp;million cases respectively. Africa has so far recorded over 8\u0026nbsp;million confirmed cases and 201,576 deaths. South Africa, Morocco and Tunisia were the most affected countries in Africa [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. As of 8th September, 2021, Uganda had a cumulative total of 99,701 confirmed cases of COVID-19 and 3031 deaths [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFrequent hand washing with soap or an alcohol based hand rub; use of face masks; maintaining physical distance; covering the mouth and nose when sneezing or coughing; and avoiding touching the mouth, eyes and nose with unwashed hands were the recommended and widely adopted individual prevention measures for COVID-19 globally [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. To reduce community spread of COVID-19, several countries, Uganda inclusive, enforced physical distance, and instituted countrywide lockdowns that involved closing schools and international airports, restricted movement of people, and closure of workplaces, among other restrictions [\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. All these individual and community prevention measures were effective in reducing the number of COVID-19 infections though they had severe consequences on people\u0026rsquo;s social, economic, health and psychological wellbeing [\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn Uganda, the first case of COVID-19 was reported on March 21, 2020 [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Restrictions including a total lockdown were instituted on April 1, 2020 with closure of schools, public transport and formal workplaces except those offering essential services. In addition, the public was encouraged to practice hand hygiene, social/physical distancing and use face masks in public spaces [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. However, there are concerns worldwide that most of the interventions have been \u0026ldquo;top-down\u0026rdquo; and may not have been appropriate to the local people in different contexts and likely led to negative socio-economic impact on the vulnerable groups in the communities [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. This has led to several unintended consequences and increased vulnerability in different populations [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. A body of literature exists on how public health measures negatively impact communities [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Unintended consequences normally result from poor policy design, unclear policy goals and inappropriate evidence use [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Identifying negative unintended consequences helps in mitigating the effects and planning for prevention of the same.\u003c/p\u003e \u003cp\u003eA study on the socio-economic vulnerability to COVID-19 in the Greater Kampala Metropolitan Area in Uganda showed slum dwellers as the most vulnerable group with a low adaptive capacity [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. A similar study among urban refugees living in slums in Uganda revealed increased income insecurity, sexual and gender-based violence and anxiety during the lockdown [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. The impact of COVID-19 among the local Ugandan slum dwellers is likely to be much more since they had no organised financial benefits from the government or international relief aid compared to the refugees. Slums in Kampala are characterized by overcrowding with many people living together and in close quarters which makes practicing social distancing, a critical prevention strategy in combating COVID-19, problematic. In addition, slums lack access to adequate basic services such as sanitation, water, food and basic health care services which further increases their vulnerability [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. This study assessed unintended socio-economic and health consequences due to the COVID-19 pandemic and the mitigation measures in slums in Kampala to draw lessons to inform the on-going and future pandemic response strategies.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eStudy setting \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was conducted in Bwaise I and Bwaise III slums of Kawempe division, Kampala Uganda from October to December 2020. Bwaise is one of the largest slum areas in Kampala with a mixture of commercial, industrial and residential settlements. Bwaise I slum has a total population of 37,500 and an average household size of 5. Bwaise III has a population of 35,000 people and also an average household size of 5 as well [18]. The two slums are characterised by poor infrastructure and service provision which creates poor housing, flooding and challenges in access to water, sanitation and hygiene [16]. The two slums are located within the Kampala Central business District (CBD) which has a high COVID-19 exposure index [14]. According to a study on the socio-economic vulnerability to COVID-19 in the Greater Kampala Metropolitan Area, Bwaise I and Bwaise III slums had the lowest adaptive capacity. Adaptive capacity in this study was assessed in terms of food security, level of income and access to good health care [14]. The study was conducted in October to December 2020, after the first lockdown was lifted on most activities except a few like bars and sports activities.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStudy design and population\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis was a mixed methods cross-sectional study using a sequential explanatory approach. Qualitative data was collected for triangulation and to complement findings from the quantitative study.\u0026nbsp;The study participants included household heads of slum dwellers aged 18 years and above for the quantitative component, and community health workers and purposively selected community members for the qualitative study. In the qualitative study, we used focus group discussions (FGDs) and photovoice. Photovoice is a visual qualitative method used in\u0026nbsp;community-based participatory research\u0026nbsp;to document insights and perspectives which raise awareness of hidden or overlooked issues and aspects of the community [19].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSample size and sampling procedure\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 425 respondents were randomly selected for the face-to-face quantitative interviews using systematic sampling. This sample size was calculated using the Kish Leslie (1964) formula for cross sectional studies and the following assumptions were considered; a conservative proportion of 50% had been done at the time of the study, confidence level of 95%, power of 80%, and a non-response rate of 10%.\u003c/p\u003e\n\u003cp\u003eIn each zone, we listed all the households with the help of the local chairperson and determined the \u0026lsquo;\u003cem\u003ek\u003c/em\u003eth\u0026rsquo; interval,\u0026nbsp;\u003cem\u003ek\u003c/em\u003e\u0026nbsp;being the total number of households in the zone divided by the sample size of households needed in that zone. To select a starting point, we stood at the centre of the zone with guidance from the local chairperson and randomly selected the starting household using a table of random numbers. Subsequent households were selected using the \u0026ldquo;\u003cem\u003ek\u003c/em\u003eth\u0026rdquo; number.\u003c/p\u003e\n\u003cp\u003eSix FGDs were conducted with purposively selected participants based on those who are more knowledgeable and well versed with community wellbeing such as local leaders and elders.\u003c/p\u003e\n\u003cp\u003eFor the photovoice method, we selected eight Community Health Workers (CHWs) as the photographers\u0026mdash;four CHWs (two females and two males) were identified in each of the two study areas. The CHWs were identified with the help of other CHWs and the local political leaders in the study areas. Selection of the CHWs was based on their area of jurisdiction, level of education, occupation and marital status to ensure diverse representation and capturing of rich photographs from their areas of influence [20].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData collection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInterviewer administered face-to-face interviews were conducted with household heads using a semi-structured questionnaire in the local language, Luganda, to assess the unintended socio-economic and health consequences due to the COVID-19 pandemic and response activities. Eight research assistants with research experience in quantitative data collection were recruited and trained to do the data collection. The questionnaire was uploaded on the Kobocollect toolbox mobile phone application and mobile phones were used for data collection. In case the kth household selected was closed on the day of data collection or if there was no proxy respondent, we rescheduled the interview for the following day and if on two subsequent times there was no respondent, we considered the next house in the same direction.\u003c/p\u003e\n\u003cp\u003eWe also conducted six FGDs in Luganda, the local language, to further assess community socio-economic and health consequences due to COVID-19 and response activities. By the 6\u003csup\u003eth\u003c/sup\u003e FGD, there was no more new information arising from the interviews. The FGDs were conducted within 50 minutes to 1 hour with 7-8 participants per session using a guide. Two FGDs included only male participants; two had only female participants while two had both male and female participants. Each FGD was moderated by a researcher experienced in conducting FGDs, key notes taken, and the discussion audio recorded.\u003c/p\u003e\n\u003cp\u003eFor photovoice, we used photographs to explore the immediate socio-economic and health consequences due to COVID-19 and response activities. Using a guide\u003cem\u003e, \u003c/em\u003ethe selected CHWs were trained in data collection using photography. The training covered study objectives, ethics in photography, use and care of cameras, professionalism and obtaining informed consent before taking the photographs. The training on ethics was guided by findings from a study which explored ethical considerations in the work of a CHW [21]. The research team conducted onsite supervision during photography to review the photos to ensure appropriate and clear photos.\u003c/p\u003e\n\u003cp\u003eThe CHWs took as many photographs as possible in one month to capture situations in their communities that were related to socio-economic and health consequences arising from the COVID-19 pandemic and response activities. A field guide with pre-determined themes was used to guide the photography. Photographers were however at liberty to take photos related to the study even if they did not fall under any pre-determined theme. Four (4) weekly meetings lasting approximately 3-4 hours were held every Saturday with CHWs and the research team to discuss the photos taken during the previous week. The number of weekly meetings was dependant on theoretical content saturation. In the weekly meetings, each CHW was asked to talk about their photographs and discuss how the pictures related to their lives and those of the community, and how they related to the pre-determined themes of the study. The meetings were moderated by a researcher with experience in using photovoice, and notes of emerging issues taken by a note taker. All discussions for the meetings were audio-recorded. All photos taken in the study were presented back to the CHWs at the end and they were asked to identify themes arising. The CHWs then grouped the photos per theme and selected photos that best represent each theme and their community through consensus.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData management and analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll study tools were pretested in a similar setting and adjusted accordingly prior to data collection to ensure they yielded the information required. Meetings were also held at the end of each day to check for consistency, completeness, and to ensure proper data collection. The study tool on the phone was fitted with checks to ensure data completeness and accuracy. All data were stored in password protected computers with no personal identifiers. Data from Kobocollect was downloaded from the app into an excel file, cleaned and imported into Stata version 14.0 for further cleaning and analysis. Quantitative data were analysed descriptively generating frequencies and proportions. To measure the association between socio-demographics and limited access to food during the COVID-19 pandemic variable, we ran a modified Poisson regression via generalized linear models to obtain prevalence ratios (PRs). Prevalence ratios were most preferred over odds ratios because the proportion of our outcome variable was \u0026gt;10%, which would have given biased estimates [22]. Variables that had\u0026nbsp;\u003cem\u003ep\u003c/em\u003e\u0026nbsp;values of up to 0.2 and those known from literature to be associated with limited access to food during disease outbreaks were included in the multivariable model. All inferential statistics were achieved at 95% confidence interval and 5% alpha level.\u003c/p\u003e\n\u003cp\u003eAudio recordings from the FGDs and photovoice meetings were transcribed verbatim in their original language of recording and translated to English if they were conducted in the local language. Three researchers read through the transcripts several times to familiarise themselves with the data after which they developed a codebook. This was followed with line by line coding by the three independent people. The independent lists of codes from the three researchers were reviewed by two core study team members to assess intercoder agreement. Any discrepancies were clarified and resolved by comparing each coder\u0026rsquo;s results with raw data until consensus was reached. Coded transcripts were then uploaded into the qualitative analysis software ATLAS.ti Version 7 for thematic analysis using the deductive and inductive approaches. Quotes were then selected to represent the main themes emerging from the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical considerations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe obtained ethical approval from the Makerere University School of Public Health Higher Degrees and Research Ethics Committee \u003cem\u003e(HDREC No.877)\u003c/em\u003e and the Uganda National Council of Science and Technology \u003cem\u003e(registration number SS638ES)\u003c/em\u003e. Written informed consent was obtained from all study participants before data collection. No photographs identifying an individual were used without the written consent of both the photographer and the identified person. The study team was trained to adhere to the COVID-19 prevention measures during field engagements and constantly supervised for compliance.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n\u003ch2\u003eSocio-demographic characteristics of the respondents\u003c/h2\u003e\n\u003cp\u003eOut of the 425 respondents for the face-to-face interviews, most were females (66.4%; 282/425); aged 26 to 33 years (26.8%; 114/425); had attained secondary as their highest level of education (46.6%; 198/425); and were Muslims (32%; 136/425). Sixty three percent (268/425) of the respondents reported earning an average of between 50\u0026ndash;300,000 Ugandan shillings (less than 100 dollars) per month \u003cem\u003e(\u003c/em\u003eTable\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cem\u003e).\u003c/em\u003e\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab1\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eSocio-demographic characteristics of the respondents\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eVariable\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eFrequency (n\u0026thinsp;=\u0026thinsp;425)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003ePercentage (%)\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSex\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMale\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e143\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e33.65\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFemale\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e282\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e66.35\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAge (years)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e18 to 25\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e78\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e18.35\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e26 to 33\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e114\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e26.82\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e34 to 41\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e96\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e22.59\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e42 to 49\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e65\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e15.29\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026ge; 50\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e72\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e16.94\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMean (SD)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e37.22\u0026thinsp;\u0026plusmn;\u0026thinsp;12.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHighest level of education\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNo formal education\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e42\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e9.88\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePrimary\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e155\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e36.47\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSecondary\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e198\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e46.59\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTertiary\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e30\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7.06\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMarital status\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMarried\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e166\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e39.06\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSingle\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e94\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e22.12\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCo-habiting\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e76\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e17.88\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDivorced / separated\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e59\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e13.88\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eWidowed\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e30\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7.06\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eReligion\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAnglican\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e131\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e30.82\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCatholic\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e99\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e23.29\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMuslim\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e136\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e32\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSeventh Day Adventist\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.88\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePentecostal\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e41\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e9.65\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eOthers\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.35\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eOccupation\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCasual labourer\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e46\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e10.82\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eEmployed\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e44\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e10.35\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSelf-employed\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e221\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e52\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNone\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e113\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e26.59\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eOthers\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.24\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eAverage income earned per month (Ugandan shilling)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e50\u0026ndash;300,000/=\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e268\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e63.06\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e300,001- 500,000/=\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e41\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e9.65\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e500,001\u0026ndash;1,000,000/=\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.47\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNone\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e114\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e26.82\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003c/div\u003e\n\u003ch2\u003eSocio-economic And Health Impact\u003c/h2\u003e\n\u003cp\u003eMost respondents reported: limited access to food (71.1%; 302/425); disruption in education (77.1%; 270/350); a drop in daily income and wages (86.1%; 329/382); loss of employment, (63.1; 125/198); limited access to cooking energy (52.7%; 224/425); and limited access to transport (68.5%; 291/425). Most respondents mentioned no impact of COVID-19 on: access to water (65.9%; 280/425); sanitation and hygiene facilities (68.7%; 292/425); and access to health care services (71.5%; 304/425). Twenty five percent of the respondents 25.4%; 86/338) reported domestic violence. Almost half (40.2%; 171/425) of the respondents reported mental health challenges including reduced sleep, anxiety and urge to drug use (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cem\u003e)\u003c/em\u003e.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab2\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eImmediate socio-economic and health consequences due to COVID-19 in Bwaise I and Bwaise III, Kampala Uganda\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eImpact on:\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eHigh\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eModerate\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eLow\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eNo impact\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHousehold access to food\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e302 (71.06)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e41 (9.65)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e20 (4.71)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e62 (14.59)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHousehold access to water\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e96 (22.59)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e28 (6.59)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e21 (4.94)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e280 (65.88)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHousehold access to sanitation and hygiene services\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e82 (19.29)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e31 (7.29)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e20 (4.71)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e292 (68.71)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eEducation (n\u0026thinsp;=\u0026thinsp;350)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e270 (77.14)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e9 (2.57)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e4 (1.14)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e67 (19.14)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHousehold daily wages and incomes (n\u0026thinsp;=\u0026thinsp;382)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e329 (86.13)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e21 (5.50)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e4 (1.05)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e28 (7.33)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eEmployment (n\u0026thinsp;=\u0026thinsp;198)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e125 (63.13)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e10 (5.05)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e8 (4.04)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e55 (27.78)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDomestic violence (n\u0026thinsp;=\u0026thinsp;338)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e86 (25.44)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e22 (6.51)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e21 (6.21)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e209 (61.83)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSocial behaviours\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e40 (9.41)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e8 (1.88)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e7 (1.65)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e370 (87.06)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFamily welfare\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e118 (27.76)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e30 (7.06)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e25 (5.88)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e252 (59.29)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHousehold lighting\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e136 (32.00)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e32 (7.53)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e26 (6.12)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e231 (54.35)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHousehold cooking energy\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e224 (52.71)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e34 (8.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e17 (4.00)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e150 (35.29)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTransport\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e291 (68.47)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e22 (5.18)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e22 (5.18)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e90 (21.18)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHealth\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e87 (20.47)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e43 (10.12)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e17 (4.00)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e278 (65.41)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAccess to health care\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e89 (20.94)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e19 (4.47)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e13 (3.06)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e304 (71.53)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMental health\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e171 (40.24)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e27 (6.35)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e23 (5.41)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e204 (48.00)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eFrom the analysis of FGDs and photovoice findings, the following themes emerged under socio-economic and health consequences due to COVID-19 and response activities; limited access to food; negative impact on children rights and education; poor housing and lack of accommodation; negative social behaviours; negative impact on family and child care; reduced income and employment; and negative impact on health and access to health care services.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFactors associated with one of the highest reported impact on socio-economic and health vulnerabilities due to COVID-19 in Bwaise I and Bwaise III, in Kampala Uganda\u003c/strong\u003e\u003c/p\u003e\n\u003ch2\u003eImpact On Household Access To Food\u003c/h2\u003e\n\u003cp\u003eAfter adjusting for potential confounders, respondents aged 25 to 33 years (adjusted PR\u0026thinsp;=\u0026thinsp;1.19, 95% CI: 1.01\u0026ndash;1.41); 42 to 49 years (adjusted PR\u0026thinsp;=\u0026thinsp;1.22, 95% CI: 1.01\u0026ndash;1.47); and \u0026ge;\u0026thinsp;50 (adjusted PR\u0026thinsp;=\u0026thinsp;1.22, 95% CI: 1.01\u0026ndash;1.48) were more likely to have limited access to food. Respondents who reported earning an average monthly income of 300,001/= and above were 0.74 times less likely to have limited access to food (adjusted PR\u0026thinsp;=\u0026thinsp;0.74, 95% CI: 0.55\u0026ndash;0.98), see Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab3\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eCrude and adjusted factors associated with the impact of COVID-19 on household access to food and socio-demographic characteristics\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eAttributes\u003c/p\u003e\n\u003c/th\u003e\n\u003cth colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eImpact of COVID-19 on household access to food\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eUnadjusted PR\u003c/p\u003e\n\u003cp\u003e(95% CI)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eAdjusted PR\u003c/p\u003e\n\u003cp\u003e(95% CI)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eP value\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eLow (n\u0026thinsp;=\u0026thinsp;82)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eHigh (n\u0026thinsp;=\u0026thinsp;343)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eP value\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSex\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMale\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e29 (20.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e114 (79.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.98 (0.89\u0026ndash;1.09)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.03 (0.93\u0026ndash;1.15)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.542\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFemale\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e53 (18.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e229 (81.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAge (years)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e18 to 25\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e23 (29.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e55 (70.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e26 to 33\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e19 (16.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e95 (83.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.18 (1.01\u0026ndash;1.39) *\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.19 (1.01\u0026ndash;1.41)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.044\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e34 to 41\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e17 (17.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e79 (82.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.16 (0.98\u0026ndash;1.38)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.18 (0.99\u0026ndash;1.41)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.063\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e42 to 49\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e10 (15.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e55 (84.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.20 (1.01\u0026ndash;1.43) *\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.22 (1.01\u0026ndash;1.47)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.038\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026ge; 50\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e13 (18.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e59 (81.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.16 (0.97\u0026ndash;1.39)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.22 (1.01\u0026ndash;1.48)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.037\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHighest level of education\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNo formal education\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7 (16.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e35 (83.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePrimary\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20 (12.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e135 (87.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.05 (0.90\u0026ndash;1.21)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.05 (0.91\u0026ndash;1.21)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.496\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSecondary\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e45 (22.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e153 (77.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.93 (0.79\u0026ndash;1.08)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.96 (0.82\u0026ndash;1.12)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.596\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTertiary\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e10 (33.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20 (66.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.80 (0.60\u0026ndash;1.07)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.84 (0.61\u0026ndash;1.15)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.270\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMarital status\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMarried\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e42 (17.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e200 (82.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSingle\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e22 (23.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e72 (76.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.93 (0.82\u0026ndash;1.05)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.99 (0.87\u0026ndash;1.12)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.868\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDivorced / separated\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e12 (20.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e47 (79.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.96 (0.84\u0026ndash;1.11)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.93 (0.81\u0026ndash;1.07)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.496\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eWidowed\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6 (20.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e24 (80.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.97 (0.80\u0026ndash;1.17)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.89 (0.74\u0026ndash;1.07)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.225\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eOccupation before\u003c/p\u003e\n\u003cp\u003epandemic\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCasual labourer\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7 (15.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e39 (84.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eEmployed\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e13 (29.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e31 (70.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.83 (0.66\u0026ndash;1.04)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.88 (0.70\u0026ndash;1.11)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.277\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSelf-employed\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e44 (19.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e178 (80.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.95 (0.82\u0026ndash;1.09)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.97 (0.84\u0026ndash;1.12)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.700\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNone\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e18 (15.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e95 (84.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.99 (0.86\u0026ndash;1.15)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.88 (0.72\u0026ndash;1.08)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.225\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eAverage monthly income\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNone\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e16 (14.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e98 (86.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e50\u0026ndash;300,000/=\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e53 (19.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e215 (80.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.93 (0.85\u0026ndash;1.03)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.84 (0.69\u0026ndash;1.01)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.060\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e300,001- above\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e13 (30.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e30 (69.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.81 (0.66\u0026ndash;1.00)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.74 (0.55\u0026ndash;0.98)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.035\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eUnintended immediate social consequences due to COVID-19 and response activities\u003c/strong\u003e\u003c/p\u003e\n\u003ch2\u003eNegative Impact On Children Rights And Education\u003c/h2\u003e\n\u003cp\u003eClosure of schools due to COVID-19 with no clear mechanism of continued learning at home exposed most children to several consequences. Photovoice participants noted that some children were exposed to forced labour either to provide extra income to the family or as their own initiative. Engagement of children in labour was mentioned by participants as likely to expose them to COVID-19, sexual violence, early pregnancies, undesirable behaviours and increase school dropout. A photographer explained the extent of the impact on children rights and education.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026ldquo;Many children have become involved in petty trade and most of these are unwilling to return to school. I am sure a substantial percentage of these children will drop out of school when schools fully reopen. Sending children especially girls to sell merchandise is problematic because they may get molested or sexually assaulted by the men they find along the way\u0026rdquo;\u003c/em\u003e (Photographer 3, female, age 38)\u003c/p\u003e\n\u003cp\u003eParticipants in both the FGDs and photovoice mentioned increased teenage pregnancies and early child marriages since the onset of COVID-19 (Photo 1). This was attributed to teenage girls being out of school and redundant at home with their parents and guardians focused on making income for survival. Unwanted pregnancies were also attributed to the girls lacking basic needs hence looking out to men for survival.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026ldquo;My issue is that since schools were closed during COVID-19 outbreak, we saw many girls drop out of school. These girls have got unwanted pregnancies and as a mother, I can\u0026rsquo;t take care of the pregnant girl and the unborn baby because I have no money or a job. I could have taken care of the pregnant girl but the workplaces were closed. We have been affected so much by this situation.\u0026rdquo;\u003c/em\u003e (Female FGD, Participant 2, Bwaise III)\u003c/p\u003e\n\u003ch2\u003eLimited access to food\u003c/h2\u003e\n\u003cp\u003eMany study participants in the FGDs and photovoice mentioned reduced access to food given that most had their income reduced, lost jobs and some had their businesses shut down during the pandemic. Reduced access to food was expressed in terms of no money to buy the food, increased food prices and limited availability of certain foods. Patients suffering from chronic illnesses were affected more because they had to take their medication on an empty stomach. Most participants mentioned reduced: frequency of meals, eating of a balanced diet and portions (Photo 2) as a coping strategy.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026ldquo;\u0026hellip;COVID-19 affected me so much because I was used to eating two meals a day but I can no longer do that. We now have one meal a day and that is supper. We take a cup of tea a day at 4pm and prepare the little food we have. At 7pm, we have our supper and sleep. The earnings also reduced.\u0026rdquo;\u003c/em\u003e (Female FGD, Participant 8, Bwaise III)\u003c/p\u003e\n\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\n\u003ch2\u003eImpact on family and child care\u003c/h2\u003e\n\u003cp\u003eCases of domestic violence in the slum communities were mentioned to have increased during the COVID-19 pandemic. Participants attributed this to no money to sustain homes, increased leisure time at home and loss of jobs by the bread winners. Relatedly, some families were said to have broken up due to the heightened violence and also increased demands for basic needs from the family.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026ldquo;\u0026hellip; I might even shed a tear while talking. First of all, i was beaten up during that time (lockdown). I was beaten up because I had no money. The child would ask me for food but I had nothing. My husband would ask for food and later beat me up. There is nothing I gained from the situation except being beaten up.\u0026rdquo;\u003c/em\u003e (Female FGD, Participant 4, Bwaise III)\u003c/p\u003e\n\u003c/div\u003e\n\u003ch2\u003eIncreased Drug Use And Abuse\u003c/h2\u003e\n\u003cp\u003eStudy participants in the photovoice also noted an increase in the number of people using drugs since the beginning of the lockdown (Photo 3). Most people are cited drinking alcohol from early morning hours to evening and others smoking cannabis and marijuana, with some developing mental illnesses. Some photovoice participants attributed the increase in drug use to increased stress in the population due to loss of jobs and income and others attributed it to several people having too much time and idleness, most of them having lost jobs and businesses.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026ldquo;\u0026hellip;the truth is we have had a rising number of such cases (cases of drug abusers) due to COVID-19 situation. Because, they (community members) searched for what to do and failed to get a job. They looked for money and what to eat and failed to get so they got frustrated and started drugs. That was a sensible person (photo 5) before COVID-19 situation but now, see what he has become.\u0026rdquo;\u003c/em\u003e (Photographer 7, male, age 32)\u003c/p\u003e\n\u003ch2\u003eUnintended Immediate Economic Consequences Due To Covid-19\u003c/h2\u003e\n\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\n\u003ch2\u003eReduced income and loss of employment\u003c/h2\u003e\n\u003cp\u003eMost participants in photovoice and FGD mentioned loss of employment as one of the consequences of COVID-19. The loss of employment was largely a result of most companies laying off staff and others because of the shutdown of businesses during the lockdown. Loss of employment was said to have greatly impacted access to basic needs and family stability.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026ldquo;\u0026hellip;people lost jobs, curfew also affected food sellers because customers were limited, those with bars sent away many workers who are now jobless; those who have lodges aren\u0026rsquo;t functional yet it also employed many people; boda-boda riders were affected by curfew as well, schools were also affected so much.\u0026rdquo;\u003c/em\u003e (Male FGD, Participant 1, Bwaise III)\u003c/p\u003e\n\u003cp\u003eDuring the lockdown and after, several businesses in the community collapsed and others had reduced performance in terms of customers and income generation. Collapse of businesses was attributed to some people using up the capital for food to survive during the lockdown and reduced performance attributed to most people having no money to buy from the business vendors.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026ldquo;COVID-19 situation affected me so much because I used to have a retail shop and the school going students would buy from me. I am a widow with many children but I had to close the shop. The little capital I had was used to buy and stock food during the COVID-19 lock down and every day would just pass by. I even lacked money to buy water and sugar.\u0026rdquo;\u003c/em\u003e (Mixed FGD, Participant 6, Bwaise III)\u003c/p\u003e\n\u003c/div\u003e\n\u003ch2\u003eInability To Afford Housing And Accommodation\u003c/h2\u003e\n\u003cp\u003eBoth photovoice and FGD participants mentioned several community members have since the start of COVID-19 accumulated rent arrears with some being evicted from the houses and shops (Photo 4). Accumulated rent arrears came because of unemployment and reduced income during the lockdown. Some community members were said to have resorted to residing in animal houses offered by neighbours.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026ldquo;This photo shows the effect of COVID-19 on housing. The property in the photo belonged to a tenant who had been evicted. The tenant had rent arrears of four months and the landlord could not tolerate him any longer. Therefore, COVID has left many people homeless.\u0026rdquo;\u003c/em\u003e (Photographer 4, male, age 64)\u003c/p\u003e\n\u003ch2\u003eUnintended Immediate Health Consequences Due To Covid-19\u003c/h2\u003e\n\u003cp\u003e\u003cstrong\u003eReduced health and limited to access health care services\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDue to limited movements during the lockdown, increased transport fares and no income, some slum dwellers resorted to not seeking health care when sick. They stayed indoors hoping to get better (Photo 5). More so, most said they were ignored and did not receive care when they visited the health centers as all attention was on COVID-19 patients. Those on chronic medication like people living with HIV, could not refill their medicines because of transport challenges.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026ldquo;Some people who had chronic illnesses such as diabetes, HIV/AIDS and hypertension either worsened or died because there was very limited access to routine healthcare services. The limited access to health care services was due to absence of transport means to health facilities and change in priority of healthcare services to mainly focus on COVID-19 patients and neglecting other diseases.\u0026rdquo;\u003c/em\u003e(Photographer 5, female, age 60)\u003c/p\u003e\n\u003cp\u003eRespondents in the FGDs reported increased mental health conditions because of COVID-19 restrictions and related challenges. Most mentioned increased stress as a result of many needs against no money; others mentioned increased anxiety and disrupted sleep.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026ldquo;We have all lost our minds during this situation. You find people walking while talking to themselves on the street. Others have tried sleeping but failed and others have got accidents because they walk without thinking. The landlords evict us and when you explain to them they also claim they built houses to make money. The children ask for food and when you talk to your husband, he just walks away. What I think is that the mental health issues will worsen in future because of this situation. People will only think 50% because of this stress.\u0026rdquo;\u003c/em\u003e (Female FGD, Participant 8, Bwaise III)\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study assessed the unintended socio-economic and health consequences due to COVID-19 and the response activities. Most respondents reported limited access to access to food, education, daily income and wages and employment, housing, mental health challenges, and increased domestic violence. Other challenges included effects on children rights and education. The unintended consequences due to COVID-19 reported in this study include critical determinants of health and pose a major threat to the wellbeing and health of these communities and could also increase their vulnerability to COVID-19.\u003c/p\u003e \u003cp\u003eOur findings revealed challenges in access to food both in terms of physical and financial access. Most respondents accessed only one meal a day, reduced portions or were not able to have a balanced diet. Slum dwellers largely depend on daily wages for food and other essential requirements [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. The prolonged lockdown without socioeconomic support therefore exposed them to severe challenges related to access to food. Uganda integrated food distribution for vulnerable urban populations to reduce the likely impact but this was not adequate in quantities and could not be sustained long enough to avert the challenges with access to food [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Our findings are similar to findings in other studies in Uganda and elsewhere where food security outcomes were worse among poor households which depend on labour income [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Limited access to food could lead to reduced nutrient intake consequently leading to diet-related and nutrition-related diseases [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Nutrition-related diseases are often associated with reduced immunity which will likely expose more people to COVID-19 and other infections [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe negative impact on children\u0026rsquo;s rights and education were raised among the challenges. COVID-19 related restrictions led to disruption of education which is likely to have long lasting impact on the children including school dropout, early pregnancies and early marriages for girls, with some unable to go back to school due to lack of school fees. Returning to school after giving birth is not guaranteed because of the stigma that could arise but also increased responsibility to take care of the child [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. In northern and eastern Uganda, an increase in cases of young girls forced to sell sex in return for cash, food, or even sanitary products during the COVID-19 pandemic was reported [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. In the Ebola outbreak in West Africa, similar consequences were observed such as teenage pregnancies, school drop outs and early marriages for school going children [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Children are vulnerable to social and health effects hence there is need to protect them from things that threaten their well being [\u003cspan additionalcitationids=\"CR35 CR36\" citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eA reduction in daily income, wages and employment was reported. Due to the lockdown, most businesses and formal workplaces were unable to operate leading to no income generation and downsizing. Studies elsewhere have reported financial insecurity, loss of employment and reduced income due to Covid related lockdowns [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan additionalcitationids=\"CR39\" citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Reduced income affects health care seeking, limited access to basic needs like food and water and increased crime rate [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. In desperation and the pursuit of income for survival, people are likely to engage in risky activities like congregating in large numbers and shunning of the recommended prevention guidelines which may lead to their exposure to COVID-19 [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Therefore, the economic and financial wellbeing of vulnerable populations should be catered for as part and parcel of the pandemic response strategies.\u003c/p\u003e \u003cp\u003eDomestic violence was reported to have increased during the COVID-19 pandemic. Increased domestic violence could have been as a result of increased financial stress in families, increased time of closed stay and unfulfilled expectations from partners. Studies elsewhere reported some people losing their lives as a result of the domestic violence, and some sustaining bruises from beatings during the COVID-19 pandemic [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. In Peru, calls of domestic violence on women to the national helpline increased by 56 percent in April 2020 [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. In northern and eastern Uganda, there was an increase in cases of young girls forced to sell sex in return for cash, food, and sanitary products [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Relatedly, the Ebola outbreak in West Africa also resulted in increased cases of gender based violence among teenage girls and young women [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Increased domestic violence threatens the wellbeing of society and family.\u003c/p\u003e \u003cp\u003eOur qualitative findings revealed limited access to health care services and worsening of some health conditions. This was reported among persons with chronic illnesses like HIV/AIDS, diabetes, hypertension and others. Studies in other countries have reported reduced health care utilisation and disrupted health care services [\u003cspan additionalcitationids=\"CR47 CR48\" citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. Reduced health care seeking may lead to poor health outcomes for other diseases and increased risk for community spread of COVID-19 and other infectious diseases due to cases not reporting to the health facilities. Strategies to strengthen and sustain other health services during pandemics such as COVID-19 are essential in ensuring good health outcomes across the board.\u003c/p\u003e \u003cp\u003eMental health challenges were also prominent in this community. Increased mental health challenges such as anxiety, disruption in sleep patterns, stress and so forth may have resulted from forced stay at home during the lockdown, separation from loved ones, restricted movements, uncertainty, boredom and fear of infection. Mental health challenges especially psychological effects have been reported elsewhere [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan additionalcitationids=\"CR51 CR52\" citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. Disease pandemics are inherently stressful hence adding other stressors such as restriction in movements, work and separation from loved ones worsen the situation, and could have longer term effects after the pandemic. Mental health challenges could also arise from the stigma that is meted on the survivors of infectious disease such as COVID-19 and their families. However, mental health is not always prioritised in disease response strategies. Pandemic response strategies should therefore integrate psychosocial and mental health interventions.\u003c/p\u003e \u003cp\u003eA strength to our study is the use of mixed methods to triangulate the unintended socioeconomic and health consequences due to COVID-19 in this vulnerable population. We used the photovoice method which enables community participation in the process and raises awareness of hidden or overlooked issues in the community. Our study however did not establish the baseline status to objectively demonstrate the changes due to COVID-19 and relied on self-reported impact. Further studies are recommended to establish the extent of impact and mitigation interventions.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe negative consequences of COVID-19 and related restrictions were quite severe among the vulnerable slum dwellers in Kampala. Most respondents reported a high impact on access to food, education, daily income and wages, employment, and access to cooking energy. Domestic violence and mental health as well as effects on child education and rights were also prominent. These findings emphasize the need for comprehensive preparedness and response strategies and plans that cater for the socioeconomic needs especially for the most vulnerable populations. During design of response and prevention activities for disease outbreaks, protocols should be established and mainstreamed to protect vulnerable groups in the community especially children and women. The impact on education and the young school going children could be long-term and requires both immediate and long-term mitigation strategies to ensure continuity of education and minimize future socioeconomic challenges.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e \u003ccolgroup cols=\"2\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCBD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCentral Business District\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCHWs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCommunity Health Workers\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCOVID-19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCoronavirus Disease\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFGDs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFocus Group Discussions\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHCD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHuman-centred design\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHDREC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigher Degrees Research and Ethics Committee\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHIV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHuman Immunodeficiency Virus\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIRB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInstitutional Review Board\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKCCA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKampala Capital City Authority\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKIIs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKey Informant Interviews\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKIs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKey informants\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNGOs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNon- Government Organisations\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSDG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSustainable Development Goal\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSOPs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStandard Operating Procedures\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUSA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnited States of America\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWHO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWorld Health Organisation\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe obtained ethical approval to conduct the study from the Institutional Review Board of Makerere University School of Public Health \u003cem\u003e(HDREC No.877)\u003c/em\u003e and registered the study with the Uganda National Council of Science and Technology \u003cem\u003e(registration number SS638ES)\u003c/em\u003e. Written informed consent was obtained from all study participants using a consent form before any data collection. Participation in the study was voluntary and participants were informed of the study procedures including the use of photographs. No photographs identifying an individual were used without the written consent of both the photographer and the identified person. All methods were carried out in accordance with guidelines and regulations from Makerere University School of Public Health and Uganda National Council of Science and Technology.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors consented to publishing this manuscript. Study participants also consented to have their information and photographs anonymously published to the wider scientific community.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData and materials supporting findings in this manuscript are available upon reasonable request through the Institutional Review Board of Makerere University School of Public Health. They can be contacted at [email protected].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Alliance for Health Policy and Systems Research, World Health Organization. The Alliance is supported through both core funding as well as project specific designated funds. The full list of Alliance donors is available here:\u0026nbsp;https://www.\u0026nbsp;who.int/alliance-hpsr/partners/en/. This work also received funding support from the Doris Duke Charitable Foundation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRN conceptualised the study and spearheaded the implementation of the study including manuscript writing. MN, JBB and SN participated in study implementation, data analysis and manuscript writing. DM and DO gave technical support of the study and manuscript writing. RW gave the overall technical oversight of the study and guided interpretation of study findings. All authors read and approved the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe acknowledge the contribution of research assistants who collected the data and the study participants who graciously responded to our questionnaires. We also acknowledge the support from the Alliance for Health Policy and Systems Research, World Health Organization and Kampala Capital City Authority during the study period.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDisclaimer:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors are themselves alone responsible for the views expressed in the Article. This article does not represent the views, decisions, or policies of the Alliance for Health Policy and Systems Research.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWHO. WHO announces COVID-19 outbreak a pandemic 2020 [updated 2020-03-12.\u003c/li\u003e\n\u003cli\u003eWHO. WHO Coronavirus (COVID-19) Dashboard: WHO; 2021 [updated 2:39pm CEST, 27 May 2021; cited 2021 25th August 2021]. Available from: https://covid19.who.int/.\u003c/li\u003e\n\u003cli\u003eWorldometer. Coronavirus Cases. 2021.\u003c/li\u003e\n\u003cli\u003eWHO. 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Owning Our Urban Future: The Case of Kampala City: A Consensus Study Report of the Committee on Urbanization in Uganda Uganda National Academy of Sciences Consensus Study Report. Uganda National Academy of Sciences, 2017.\u003c/li\u003e\n\u003cli\u003eGoU. Slum Settlements in Kampala. 2014.\u003c/li\u003e\n\u003cli\u003eWang C, Burris MA. Photovoice: Concept, methodology, and use for participatory needs assessment. Health education \u0026amp; behavior. 1997;24(3):369-87.\u003c/li\u003e\n\u003cli\u003eSutton-Brown CA. Photovoice: A methodological guide. Photography and Culture. 2014;7(2):169-85.\u003c/li\u003e\n\u003cli\u003eMusoke D, Ssemugabo C, Ndejjo R, Molyneux S, Ekirapa-Kiracho E. Ethical practice in my work: community health workers\u0026rsquo; perspectives using photovoice in Wakiso district, Uganda. BMC Medical Ethics. 2020;21(1):1-10.\u003c/li\u003e\n\u003cli\u003eTamhane AR, Westfall AO, Burkholder GA, Cutter GR. 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Teenage Pregnancy after Ebola in Sierra Leone. London: Overseas Development Institute. 2015.\u003c/li\u003e\n\u003cli\u003eOnyango MA, Resnick K, Davis A, Shah RR. Gender-based violence among adolescent girls and young women: a neglected consequence of the West African Ebola outbreak. Pregnant in the Time of Ebola: Springer; 2019. p. 121-32.\u003c/li\u003e\n\u003cli\u003eWHO. Coronavirus Disease (COVID-19) - events as they happen 2020 [updated 2020.\u003c/li\u003e\n\u003cli\u003eUNDP. Socio-economic impact of COVID-19 in Uganda: short-, medium-, and long-term impacts on poverty dynamics and SDGs using scenario anlaysis and system dynamics modeling. UNDP, 2020 2020. Report No.\u003c/li\u003e\n\u003cli\u003eUN. Everyone Included: Social Impact of COVID-19 | DISD 2020 [updated 2020.\u003c/li\u003e\n\u003cli\u003eHuang C, Wang Y, Li X, Ren L, Zhao J, Hu Y, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. The lancet. 2020;395(10223):497-506.\u003c/li\u003e\n\u003cli\u003eNicola M, Alsafi Z, Sohrabi C, Kerwan A, Al-Jabir A, Iosifidis C, et al. The socio-economic implications of the coronavirus pandemic (COVID-19): A review. International journal of surgery (London, England). 2020;78:185.\u003c/li\u003e\n\u003cli\u003eUNDP. Socio-Economic Impact of COVID-19 in Uganda. 2020 2020. Report No.\u003c/li\u003e\n\u003cli\u003eMartin A, Markhvida M, Hallegatte S, Walsh B. Socio-Economic Impacts of COVID-19 on Household Consumption and Poverty. Economics of Disasters and Climate Change. 2020:1-27.\u003c/li\u003e\n\u003cli\u003ePeters DH, Garg A, Bloom G, Walker DG, Brieger WR, Hafizur Rahman M. Poverty and access to health care in developing countries. Annals of the New York Academy of Sciences. 2008;1136(1):161-71.\u003c/li\u003e\n\u003cli\u003eBengle R, Sinnett S, Johnson T, Johnson MA, Brown A, Lee JS. Food insecurity is associated with cost-related medication non-adherence in community-dwelling, low-income older adults in Georgia. Journal of Nutrition for the Elderly. 2010;29(2):170-91.\u003c/li\u003e\n\u003cli\u003eTaylor S. The psychology of pandemics: Preparing for the next global outbreak of infectious disease: Cambridge Scholars Publishing; 2019.\u003c/li\u003e\n\u003cli\u003eRavindran S, Shah M. Unintended consequences of lockdowns: Covid-19 and the shadow pandemic. National Bureau of Economic Research, 2020 0898-2937.\u003c/li\u003e\n\u003cli\u003eAg\u0026uuml;ero JM. Covid-19 and the rise of intimate partner violence. 2020.\u003c/li\u003e\n\u003cli\u003ePellegrini M, Ponzo V, Rosato R, Scumaci E, Goitre I, Benso A, et al. Changes in Weight and Nutritional Habits in Adults with Obesity during the \u0026ldquo;Lockdown\u0026rdquo; Period Caused by the COVID-19 Virus Emergency. Nutrients. 2020;12(7):2016.\u003c/li\u003e\n\u003cli\u003eGhosal S, Sinha B, Majumder M, Misra A. Estimation of effects of nationwide lockdown for containing coronavirus infection on worsening of glycosylated haemoglobin and increase in diabetes-related complications: a simulation model using multivariate regression analysis. Diabetes \u0026amp; Metabolic Syndrome: Clinical Research \u0026amp; Reviews. 2020.\u003c/li\u003e\n\u003cli\u003eBodrud-Doza M, Shammi M, Bahlman L, Islam ARMT, Rahman MM. Psychosocial and Socio-Economic Crisis in Bangladesh Due to COVID-19 Pandemic: A Perception-Based Assessment. Frontiers in public health. 2020;8(341).\u003c/li\u003e\n\u003cli\u003eWHO. COVID-19 significantly impacts health services for noncommunicable diseases 2020 [updated 2020.\u003c/li\u003e\n\u003cli\u003eDuan L, Zhu G. Psychological interventions for people affected by the COVID-19 epidemic. The Lancet Psychiatry. 2020;7(4):300-2.\u003c/li\u003e\n\u003cli\u003eDubey S, Biswas P, Ghosh R, Chatterjee S, Dubey MJ, Chatterjee S, et al. Psychosocial impact of COVID-19. Diabetes \u0026amp; Metabolic Syndrome: Clinical Research \u0026amp; Reviews. 2020.\u003c/li\u003e\n\u003cli\u003eCellini N, Canale N, Mioni G, Costa S. Changes in sleep pattern, sense of time and digital media use during COVID‐19 lockdown in Italy. Journal of Sleep Research. 2020:e13074.\u003c/li\u003e\n\u003cli\u003eJaved B, Sarwer A, Soto EB, Mashwani ZU. The coronavirus (COVID-19) pandemic's impact on mental health. The International journal of health planning and management. 2020;35(5):993-6.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Photovoice, unintended consequences, COVID-19, Slum dwellers","lastPublishedDoi":"10.21203/rs.3.rs-891320/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-891320/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eTo reduce the spread of COVID-19, several countries in Africa instituted countrywide lockdowns and other public health measures. Whereas lockdowns contributed to the control of the pandemic, there were concerns about the unintended consequences of these measures especially in the most vulnerable populations. We assessed unintended socio-economic and health consequences due to the COVID-19 pandemic and the mitigation measures in slums in Kampala to inform the on-going and future pandemic response strategies.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eThis was a mixed methods cross-sectional study conducted in Bwaise I and Bwaise III slums of Kawempe division, Kampala Uganda from October to December 2020. We used systematic sampling to randomly select 425 household heads for the face-to-face quantitative interviews. We also conducted six focus group discussions (FGDs) with slum dwellers and used photovoice among eight Community Health Workers (CHWs) to document unintended socio-economic and health consequences. Quantitative data were imported into STATA version 14.0 for analysis, while qualitative data were analysed thematically using NVivo version 12. Modified Poisson regression analysis was conducted to establish factors associated with impact on access to food.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eMost respondents reported limited access to food (71.1%; 302/425); disruption in education (77.1%; 270/350); drop in daily income and wages (86.1%; 329/382) and loss of employment (63.1; 125/198). Twenty five percent of the respondents (25.4%; 86/338) reported domestic violence as one of the challenges. Seven themes emerged from the qualitative findings on the impact of COVID-19 including: limited access to food; negative impact on children’s rights (child labour and early pregnancies) and education; poor housing and lack of accommodation; negative social behaviours; negative impact on family and child care; reduced income and employment; and negative impact on health and access to health care services. \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConclusion \u003c/strong\u003e\u003c/p\u003e\u003cp\u003eThe slum dwellers of Bwaise I and Bwaise III experienced several negative socio-economic consequences of COVID-19 and its prevention measures that severely affected their wellbeing. Children experienced severe consequences such as child labour and early pregnancies among the girls. Response activities should be contextualised to different settings and protocols to protect the vulnerable groups in the community such as children and women should be developed and mainstreamed in response activities.\u003c/p\u003e","manuscriptTitle":"Unintended Socio-Economic and Health Consequences of COVID-19 among Slum Dwellers in Kampala, Uganda","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2021-09-21 15:16:43","doi":"10.21203/rs.3.rs-891320/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2021-10-26T04:56:52+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2021-10-23T09:06:07+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2021-09-22T15:36:57+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"8e6033c9-6372-4fd0-9fd4-f8402787c81f","date":"2021-09-21T11:49:47+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"a03ef6a4-3a7d-44bd-a1dc-90466dfc4d0a","date":"2021-09-19T15:40:37+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2021-09-19T14:44:26+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2021-09-19T14:29:21+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2021-09-16T14:17:59+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2021-09-16T14:15:55+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Public Health","date":"2021-09-09T16:14:15+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"05dea38a-a3c8-4b5e-9f25-c3493727e836","owner":[],"postedDate":"September 21st, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":7329278,"name":"Health Policy"}],"tags":[],"updatedAt":"2022-01-13T21:48:59+00:00","versionOfRecord":{"articleIdentity":"rs-891320","link":"https://doi.org/10.1186/s12889-021-12453-6","journal":{"identity":"bmc-public-health","isVorOnly":false,"title":"BMC Public Health"},"publishedOn":"2022-01-13 21:48:59","publishedOnDateReadable":"January 13th, 2022"},"versionCreatedAt":"2021-09-21 15:16:43","video":"","vorDoi":"10.1186/s12889-021-12453-6","vorDoiUrl":"https://doi.org/10.1186/s12889-021-12453-6","workflowStages":[]},"version":"v1","identity":"rs-891320","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-891320","identity":"rs-891320","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}