Prevention of cholera and COVID-19 pandemics in Uganda: understanding vaccine coverage survey Plus

doi:10.21203/rs.3.rs-1997127/v1

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Research Article

Prevention of cholera and COVID-19 pandemics in Uganda: understanding vaccine coverage survey Plus

https://doi.org/10.21203/rs.3.rs-1997127/v1

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Journal Publication

published 21 Jul, 2023

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Background

Between March, 2020 and December, 2021, Uganda experienced high prevalence of cholera and Coronavirus Disease 2019 (COVID-19) leading to 1,534 cholera cases with 14 deaths and 136,065 COVID-19 cases with 3,285 deaths reported respectively. This study investigated mass vaccination campaigns for the prevention of the two pandemics namely Oral Cholera Vaccine (OCV) and COVID-19 vaccine coverages; Adverse Events Following Immunization (AEFI); barriers and enablers for the vaccine uptake and the feasibility of incorporating Water, Sanitation and Hygiene (WASH) assessments into vaccine coverage surveys.

Methods

A household survey was conducted between January and February, 2022 in the six districts of Uganda which had recently conducted OCV mass vaccination campaigns or had ongoing COVID-19 mass vaccination campaigns. The survey randomly enrolled 900 households with 4,315 persons of whom 2,085 were above 18 years. Data were collected and analysed using STATA statistical package. Frequencies, percentages, Odds ratios, confidence intervals and maps were generated and interpreted.

Results

The OCV coverage for dose one and two were 85% (CI: 84.2–86.4) and 67% (CI: 65.6–68.4) respectively. Among the 4,315 OCV recipients, 2% reported mild AEFI, 0.16% reported moderate AEFI and none reported severe AEFI. The COVID-19 vaccination coverage for dose one and two were 69.8% (CI: 67.8–71.8) and 18.8% (CI: 17.1–20.5) respectively. Approximately, 23% (478/2,085) of COVID-19 vaccine recipient reported AEFI; 94% were mild, 0.6% were moderate and 2 cases were severe. The commonest reason for missing COVID-19 vaccine was fear of the side effects. For most districts (5/6), sanitation (latrine/toilet) coverages were low at 7.4% − 37.4%.

Conclusion

There were high OCV coverages but low COVID-19 vaccine and sanitation coverages with high number of moderate cases of AEFI recorded due to COVID-19 vaccines. The low COVID-19 coverage could indicate vaccine hesitancy for COVID-19 vaccines. Furthermore, incorporation of WASH assessment in the OCV coverage surveys is recommended for similar settings to generate data for better planning. However, more studies are required on COVID-19 vaccine hesitancy.

COVID

vaccine

cholera

Africa

pandemic

Uganda

health

water

sanitation

coverage

Cholera and Coronavirus disease 2019 (COVID-19) are the two ongoing devastating pandemics in sub-Saharan Africa [1, 2] that have a common origin in Asian continent [3, 4]. Cholera is a diarrheal disease caused by a bacteria Vibrio cholerae [5]. It is an old disease, with seven recorded pandemics [6]. The seventh cholera pandemic started in 1961, in Indonesia and is responsible for the reported cases and deaths [7]. In developed countries cholera was eliminated over a half a century ago [8]. However, cholera remains a big threat causing many deaths especially in sub-Saharan Africa and some parts of Asian continent [9]. In 2020, 27 countries reported a total of 323,320 cholera cases and 857 deaths [10]. Cholera is transmitted through faeco-oral route [11]. Prevention of cholera is by universal access to safe water, sanitation and hygiene (WASH) [12]. For those areas with inadequate WASH, use of oral cholera vaccine (OCV) is an important intervention to complement WASH, surveillance and case management in prevention of the cholera pandemic [13, 14]. There are three WHO pre-qualified OCVs namely, Dukoral®, Shanchol™ and Euvichol-Plus® [15]. In order to confer full protection by OCV, the person should receive two doses of a particular vaccine that are separated by at least 14 days apart [16].

On the other hand, COVID-19 is a recent disease which was first reported in Wuhan, China in December 2019 [3]. It soon spread to other parts of the world and in March 2020, COVID-19 was declared a pandemic [17]. COVID-19 is a respiratory viral disease that is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)[3]. The data show that COVID-19 affected developed countries and continents more than the countries in Africa which are still developing [18]. As of June 2022, over 515 million cases and more than 6 million deaths due to COVID-19 were confirmed and reported to the WHO [19]. SARS-CoV-2 is spreads through close contact with infected persons such as occur during the conversation [20]. The transmission of the SARS-CoV-2 from an infected person’s mouth or nose can also occur in small liquid particles, when they speak, breath, cough, sneeze or sing [20]. Moreover, just like cholera where there are asymptomatic or mild cases [21, 22], coronavirus infection also has asymptomatic and mild cases which are detected when carrying out routine testing in search for cases [23]. Majority of the COVID-19 cases with clinical disease have mild symptoms [24]. In few of the COVID-19 cases, the disease is more severe, requiring admission, oxygen therapy and intensive care [25]. Moderate and severe COVID-19 cases require hospitalization for close attention and appropriate treatment [26]. Prevention of COVID-19 spread is through isolation of confirmed cases, hand washing, wearing of masks, social distancing, quarantine and lockdown [24, 26–28]. Mass vaccination through the use of the WHO approved vaccines is another effective way to prevent COVID-19 [28].

However, the virus has many variants of the original virus which keep on evolving [29]. Notable among the variants are Alpha, beta, delta and Omicron [30–32].

While COVID-19 pandemic is a recent disease in Africa [18], the seventh cholera pandemic reached Africa in early 1970s and is endemic in sub-Saharan Africa [6, 33]. Uganda, a country in sub-Saharan Africa has been affected by both pandemics since 2020 [34, 35]. While cholera is endemic in Uganda with the records going back to over a half a century [36], COVID-19 was first confirmed in Uganda 21st March, 2020 [37]. Both pandemics can be prevented using similar approaches such as handwashing and hygiene, social distancing, restriction of large gatherings, improved general hygiene in health facilities and households, lockdown and vaccination with appropriate vaccines [38–41].

Mass vaccination with recommended vaccines of the susceptible persons in addition to implementation of other control measures are effective in reducing the incidence of both cholera and COVID-19 [41–43]. Vaccine coverage of above 50% with two doses of a particular OCV is needed to confer herd immunity to the vaccinated population [40]. For COVID-19 vaccines at least 70% coverage with two doses of the two dose vaccine is required [44]. Consequently, in order to effectively monitor vaccination programs and to establish if the protective coverages have been achieved often coverage surveys are carried out [45]. It should be noted that though OCV is effective in preventing cholera epidemics, this prevention is not permeant [40]. Often, protection with OCV lasts 3–5 years. Hence, to sustain the benefits of OCV if no improvement in WASH has been recorded in the subsequent years after the campaigns, repeat OCV mass campaigns are recommended [46].

In 2017, the WHO launched a global cholera elimination roadmap that has a target to eliminate cholera by 2030 in some partner States [14]. In this roadmap a number of interventions to reduce cholera were recommended and they included mass vaccination of the communities in cholera hotspot districts [47]. In 2017, the government of Uganda developed a five year plan [48] to guide cholera preventive activities. This plan had interventions recommended in the WHO global cholera elimination roadmap [14] such as mass vaccination with OCV for cholera hotspot districts. In 2018, Uganda applied for OCV from the World Health Organization, Global Taskforce for Cholera Control (GTFCC) and carried out a series of OCV campaigns which continued to the end of 2021. In March, 2020 the first case of COVID-19 was confirmed in Uganda and thereafter the two pandemics remained major public health issues requiring strong interventions to mitigate them. Between March, 2020 and December, 2021 at least 1,534 cases with 14 deaths of cholera [34] and 136,065 cases with 3,285 deaths of COVID-19 [49] were reported respectively. Mass vaccination using WHO recommended vaccines [42, 43] are some of the interventions that the Uganda government uses to prevent these pandemics. The currently used COVID-19 vaccines are given intramuscularly and like OCV, commonly two doses (except Jonson and Johnson vaccine where a single dose is adequate) are administered for full protection. The doses are separated by a period of not less than 21–28 days. In Uganda, the following COVID-19 vaccines have been in use namely, Astra Zeneca, Moderna, Sinovac, Sinopharm, Pfizer and Jonson and Johnson. The OCV that has been used since 2018 in Uganda is Euvichol plus (Eubiologics, Korea). However, the vaccines are known to cause mild to moderate side effects that resolve within a few days [45, 50] but these can negatively affect vaccine uptake by the communities.

On the other hand, adequate WASH services is the ultimate solution for prevention of cholera outbreaks [40] and a pillar for healthy living [51]. However, often after the OCV campaigns the coverage surveys are done [45, 52–54] without WASH assessments which are equally important to plan for the long-term (permanent) cholera prevention. Therefore, the aim of this study was to generate data to guide the government of Uganda to prevent cholera and COVID-19 pandemics by: 1) establishment of the OCV and COVID-19 vaccine coverages 2) identification of the AEFI. 3) describe the barriers and enablers for the vaccine uptake. 4) explore the feasibility of integrating WASH assessment into OCV coverage surveys in order to generate data to guide the scale-up of the long-term cholera preventive measures.

Study setting

The survey was conducted in January 2022, in the three out of the four regions of Uganda that had high risk factors of both cholera and COVID-19 pandemics. In each of these regions, two cholera hotspot districts and at high risk of COVID-19 transmission were selected. These districts (Obongi, Madi-Okollo, Busia, Namayingo, Ntoroko and Kasese) were purposely selected because they had recently completed oral cholera vaccination campaigns and or were continuing to carry out COVID-19 vaccination. These districts were all located along the international country borders and all had high risk for both cholera and COVID-19 pandemics due to frequent cross-border movements of the populations there-in. The locations of the six districts in Uganda are shown in Fig. 1.

Figure 1: Map of Uganda showing the regions of Uganda and the locations of the six districts (study area). The brown dots represent the locations of sampled households. All the six districts are located along the international borders: 1a), northern Uganda, Obongi and Madi Okollo districts; 1b), eastern Uganda, Busia and Namayingo districts and 1c), western Uganda, Ntoroko and Kasese districts.

Sample size determination

The sample size was determined using previously documented method [55]. Hence, a total of 150 respondents per district were selected giving 900 respondents for the six study districts.

Selection of the villages and respondents

The survey was conducted following similar methodology, criteria and procedures as previously described [45]. Thirty (30) clusters each consisting of 5 households were sampled from each of the six selected districts. The sampling frame consisted of all the villages in the districts where OCV was administered. A total of 30 villages were randomly selected from a frame of all villages in the district. The first task in household selection was to get sub-county population and then proportionately distribute the 30 villages according to the sub-county population. Thus, the sub-counties that had bigger population were proportionately allocated more villages (clusters). Next, in each of the selected villages, 5 households were randomly selected and the household heads interviewed according to pretested questionnaire. A total of 150 households were selected and interviewed from each of 30 villages. The questionnaire and a checklist were used to assess the status of WASH. The WASH assessment tool (questionnaire and a checklist) is shown in additional file 1.

Study variables

The study variables included:

location of the house, number of persons who lived in the household, their ages and sex, evidence of receiving the vaccine by asking for and checking the vaccination card or getting convincing explanation on what was done. Also, for those who did not receive the vaccine, the reason why the vaccine was not administered was asked and noted.

The variables to assess WASH included;

Household water: Source of household water, time spent collecting water and treatment or boiling of drinking water.

Sanitation: availability of latrine or toilet (includes latrine of all types but with washable floor, toilet and ecosan or any other recommended as safe), type of fecal disposal facility (latrine, toilet, ecosan and other appropriate one) and ownership of the latrine or toilet facility by the family.

Hygiene: availability of handwashing facility, availability of soap and for those that washed hands when hand washing was done.

Variables to identify AEFI involved asking for AEFI for each individual member of the household who received vaccines. For those with AEFIs, what was done after noticing the AEFI (reported or not reported to the health workers).

Categorization of Adverse Effects Following Immunization (AEFI)

The AEFI were categorized into three groups namely;

Mild: The person continued with the normal activities;

Moderate: The person was able to continue with most activities but the symptoms interfered somewhat and

Severe: The clinical symptoms interfered so much that the person was not able to continue with normal activities.

Data management and analysis

Data were collected and entered into a data entry application designed in KoBoToolbox [56] using mobile phones. This application was designed to avoid erroneous entries through proper validation of fields; to allow only the entry of the possible values for a field. Also, skip patterns and value labels were incorporated into the application. Data were routinely checked for errors and inconsistences which were identified and corrected. Common inconsistences were immediately communicated to field teams through their supervisors to ensure that timely action s taken to correct the error and avoid future errors. Clean datasets were backed up at the end of each data collection day on a central computer and another copy on flash drive that was kept with the data supervisor. After all data were collected and entered, they were transferred to Stata version 14 for analysis. Data were analysed to get frequencies, percentages, proportions and means. Comparisons between groups, such as sub-counties or age strata was done using Chi Square or 2 x X tables. Logistic regression was used to measure associations between OCV coverage with a set of respondents’ characteristics (predictors/factors) by generating odds ratios which are used to describe the likelihood of occurrence of an outcome in the exposed group in comparison to their unexposed counterparts. The maps were created using Arch Map software, version 10.5, Redlands, California, United States. The shapefiles used to create the maps were obtained from open-source portal of United Nations High Commission for the Refugees [57]. Geographical Positions coordinates of the households were collected for all the households sampled. These coordinates were stored and used to locate the households on the maps.

Quality assurance

To ensure quality, pretesting of study tools, training of research assistants, field supervision of research assistants by principal investigators and co-investigators, routine data cleaning and removal of identified errors and verification visits to interviewed households were carried out. In addition, daily debrief meetings were held with research assistants to discuss incidents or events which occurred during data collection. As a way of data verification, the survey supervisors revisited (15 households, about 10%) of the households after they were visited by data collectors to verify if the households were visited and interviewed. During the verification visits, no data were collected and the visits were brief lasting between twenty to thirty minutes.

Demographic characteristics of the respondents

A total of 900 households and respondents were randomly enrolled in the survey. Each of the six districts had 150 households or respondents. Overall, more than half (504, 56%) of the respondents were male. About two thirds (585, 65%) of respondents were aged 20–49 years with over a third (306, 34%) being 50 years and above. Slightly more than half (477, 53%) of the respondents attained primary level of education, over a quarter 234, 26% achieved secondary level while 117, 13% reported no formal education at all.

Oral cholera and COVID-19 vaccine coverages

Oral Cholera Vaccine Coverage

There were 4,315 household members of whom 85% received dose one of the OCV. All districts registered dose one coverage of above 79%. Obongi district registered the highest first dose coverage of 90%. Second dose coverage among these household members was 67% indicating a drop out of more than 10% between dose one and dose two. The lowest second dose coverage was recorded in Ntoroko district of 55%. The OCV vaccine coverage in the studied population in shown in Table 1.

Table 1

Oral cholera vaccine coverage by district, sex, age group and education level.
Background characteristics	received only one dose of OCV, % (95%CI)	% Received two doses of OCV % (95%CI)	% received at least one dose of OCV % (95%CI)	Number of household members (n)
Overall	18.3 (17.2–19.5)	67.0 (65.6–68.4)	85.3 (84.2–86.4)		4,315
District name
Busia	15.1 (12.4–18.2)	64.0 (60.0–67.8)	79.1 (75.6–82.2)	616
Kasese	20.7 (17.8–23.7)	64.3 (60.8–67.7)	85.0 (82.2–87.4)	751
Madi-Okollo	11.3 (9.0–13.9)	77.0 (73.7–80.1)	88.3 (85.7–90.6)	700
Namayingo	25.2 (22.0–28.6)	61.7 (58.0–65.4)	86.9 (84.1–89.3)	687
Ntoroko	25.1 (21.9–28.6)	55.4 (51.6–59.2)	80.5 (77.3–83.4)	677
Obongi	13.7 (11.5–16.1)	76.5 (73.5–79.2)	90.2 (88.0–92.0)	884
Sex
Male	18.9 (17.2–20.7)	65.8 (63.7–67.9)	84.7 (83.0–86.2)	2023
Female	17.9 (16.3–19.5)	68.0 (66.1–69.9)	85.9 (84.4–87.3)	2292
Age group
0–4	15.0 (12.2–18.3)	51.9 (47.6–56.1)	66.9 (62.8–70.8)	559
5–9	16.2 (13.4–19.3)	73.4 (69.8–76.8)	89.6 (87.0–91.8)	643
10–19	15.6 (13.5–17.9)	74.5 (71.8–77.1)	90.1 (88.2–91.8)	1095
20–29	21.7 (18.6–25.0)	63.0 (59.2–66.7)	84.7 (81.7–87.3)	665
30–39	18.4 (15.0–22.0)	66.7 (62.4–70.8)	85.1 (81.6–88.1)	502
40–49	23.7 (19.5–23.3)	65.5 (60.5–70.3)	89.2 (85.6–92.1)	380
50+	22.5 (18.8–26.5)	65.8 (61.3–70.1)	88.3 (85.1–91.1)	471
Education
None	17.4 (14.3–20.8)	65.7 (61.6–69.7)	83.1 (79.8–86.2)	552
Primary	18.6 (17.0–20.2)	68.8 (66.9–70.7)	87.4 (86.0–88.7)	2361
Secondary	16.2 (14.1–18.5)	67.2 (64.3–69.9)	83.4 (81.1–85.6)	1103
Post-Secondary	26.5 (21.0–32.9)	53.8 (47.0–60.3)	80.3 (74.6–85.3)	299

Level of awareness about the OCV campaign and knowledge on the benefits of OCV

The vast majority (92%) of household heads had ever heard about OCV and 85% had heard about the planned OCV campaigns prior to the vaccination team visiting their homes. The percentage of awareness by district were Namayingo (97%), Kasese (96%), Ntoroko (95%), Busia (91%), Obongi (87%) and Madi-Okollo (83%). The respondents also were aware of the benefits of OCV and the majority (88%) mentioned that OCV helps to prevent cholera infection, 13% mentioned that it prevents cholera outbreaks while another 5% mentioned that it prevents other diarrheal diseases.

Barriers to uptake of Oral cholera vaccine

Among the 634 persons who did not get the OCV, the most common reasons given for missing out were: the individuals had travelled away from home (38%), below age (19%) and team did not visit the household (14%). The reasons given for missing out the OCV are shown in the Fig. 2.

Figure 2: Reasons for missing oral cholera Vaccination

Determinants for the uptake of the Oral Cholera Vaccine

The OCV uptake was statistically significantly associated with the district, education level and prior awareness about the vaccination campaign. Respondents with prior awareness were 3 times more likely [OR: 3.273, CI: 2.65–4.043] to report uptake of the OCV compared to their counterparts without prior information about the vaccination campaign. In addition, uptake was higher among those with education than none. Respondents with primary education were 1.5 times more liked to receive OCV than those without education. Determinants of OCV uptake are shown in Table 2.

Table 2: Determinants of uptake of at least one dose of OCV
Characteristic	Un adjusted Odds Ratio (95% CI)	Adjusted Odds Ratio (95% CI)
District
Busia	Ref	Ref
Kasese	1.496 (1.132–1.976)	1.299 (0.966–1.747)
Madi-Okollo	1.996 (1.477–2.698)	1.894 (1.373–2.613)
Namayingo	1.757 (1.309–2.359)	1.531 (1.115–2.104)
Ntoroko	1.094 (0.833–1.435)	0.981 (0.731–1.317)
Obongi	2.427 (1.808–3.257)	2.116 (1.545–2.899)
Sex
Male	Ref	Ref
Female	1.095 (0.925–1.296)	1.113 (0.931–1.33)
Education
None	Ref	Ref
Primary	1.403 (1.088–1.808)	1.539 (1.177–2.014)
Secondary	1.019 (0.775–1.339)	1.182 (0.878–1.591)
Post Sec	0.824 (0.574–1.183)	1.168 (0.785–1.739)
Had heard about the vaccination campaign prior to the vaccination team visiting their home
No	Ref	Ref
Yes	3.256 (2.664–3.980)	3.273 (2.65–4.043)

COVID-19 vaccine coverage

There were 2,085 household members aged 18 years and above, 70% had received at least one dose of the COVID-19 vaccine. Kasese district with 95% COVID-19 dose one vaccine coverage had the highest and the lowest was in Namayingo district at 33.2%. The COVID-19 vaccine coverage by the background characteristics are shown in Table 3.

Table 3

Percentage of household members aged > 18 years that received COVID-19 vaccine
Background characteristics	% Received dose 1 of Covid-19 vaccine	% Received Dose 2 of Covid-19 vaccine		Number of households member (n)
Background characteristics	% Received dose 1 of Covid-19 vaccine	Yes	N/A	Number of households member (n)
Overall	69.8 (67.8–71.8)	18.8 (17.1–20.5)	21.4 (19.6–23.2)	2085
District name
Busia	38.2 (33.0-43.6)	21.6 (17.3–26.4)	0.3 (0.0-1.6)	338
Kasese	94.9 (92.0-96.9)	22.9 (18.6–27.6)	28.9 (24.2–33.9)	350
Madi-Okollo	88.7 (84.7–91.9)	19.8 (15.6–24.6)	46.2 (40.6–51.9)	318
Namayingo	33.2 (28.3–38.5)	12.1 (8.9–16.1)	0.0	346
Ntoroko	77.7 (72.8–82.1)	23.2 (18.8–28.1)	7.8 (5.2–11.3)	332
Obongi	84.8 (80.9–88.2)	14.2 (10.9–18.0)	42.9 (38.0-47.9)	401
Sex
Male	71.0 (67.9–73.9)	22.8 (20.1–25.6)	19.7 (17.2–22.4)	909
Female	69.0 (66.2–71.6)	15.7 (13.7–17.9)	22.8 (20.4–25.3)	1176
Age group
18–19	67.2 (54.6–78.2)	11.9 (5.3–22.1)	29.9 (19.3–42.3)	67
20–29	67.7 (64.0-71.2)	13.2 (10.8–16.0)	24.8 (21.6–28.3)	665
30–39	66.3 (62.0-70.5)	18.5 (15.2–22.2)	18.9 (15.6–22.6)	502
40–49	76.6 (72.0-80.7)	24.7 (20.5–29.4)	20.3 (16.3–24.7)	380
50+	71.5 (67.2–75.6)	23.1 (19.4–27.2)	19.1 (15.7–23.0)	471
Education
None	72.5 (66.5–77.9)	15.1 (10.9–20.2)	25.1 (19.9–30.9)	255
Primary	69.1 (66.3–71.8)	15.2 (13.1–17.4)	23.5 (21.1–26.1)	1118
Secondary	68.1 (64.0–72.0)	23.4 (19.9–27.1)	16.4 (13.4–19.8)	548
Post-Secondary	76.2 (69.0-82.5)	32.3 (25.2–40.1)	18.3 (12.7–25.1)	164

Level of awareness about the COVID-19 vaccination, treatment and benefits

A high percentage (97%) had ever heard about the COVID-19 vaccines and 89% also knew a place where treatment for COVID-19 patients was provided. This knowledge was high in all districts with Kasese (97%), Busia (97%), Ntoroko (90%), Madi-Okollo (86%), Obongi (83%) and Namayingo (78%). The majority, 83% of respondents knew the benefits of the COVID-19 vaccine and mentioned that it helps to prevent COVID-19 infection, 24% mentioned that it prevents severe infection while less than 1% mentioned that it had no benefit. The main sources of information about COVID-19 for most of the respondents were the radios (59%), local leaders (44%) and health workers (42%) as shown in Additional file 2.

Barriers to uptake of COVID-19 vaccines

The respondents were asked to give the reasons why they could not receive the vaccination. The most common response in 17% of the response for those who missed was that they were afraid of the vaccine side effects. The reasons for missing COVID-19 vaccination are shown in Fig. 3.

Figure 3: Reasons for missing COVID-19 vaccination

Distance to the nearest facility

The study found that majority (69%) of respondents travelled on foot to the nearest health facility to get the services, 25% used a bicycle or motorcycle, 3% used boats and another 3% used a taxi or bus.

Vaccine Adverse Events following Immunizations (AEFI)

Oral cholera vaccine

The percentage of persons in households who were reported to have had AEFI as a result of receiving OCV was small, 2%, 123/4,315. Among the 123 household members who reported AEFI, majority (117/123, 94%) rated the AEFI as mild, while (6%, 7/123) of the cases were moderate. There were no severe AEFI reported. The AEFI reported during the study are shown in Fig. 4.

Figure 4: Reported Adverse Events Following Immunization with COVID-19 vaccines

COVID-19 Vaccines

Among the 2,085 respondents who were above 18 years and received the COVID-19, 473 (22.69%) reported getting AEFI. Pain at the site of injection was the commonest AEFI reported in 42% of persons. Other AEFI are shown in Fig. 5.

Figure 5: Reported AEFI after COVID-19 vaccination

Among the 478 respondents who reported AEFI with the COVID-19 vaccine, the vast majority (94%) rated the AEFI as mild (resolved, a person continued with normal work), 6% (28 persons) of the cases had moderate (interfered with work but resolved without seeking care) while only one person was severe (sought care from the nearest health workers) and presented with the following severe symptoms namely: fever, vomiting and cough.

Water, sanitation and hygiene coverages

With exception of Busia districts where the WASH indicator coverages were above 89%, in the rest of the districts the latrine coverages were below 40% with the lowest of 7.4% in Madi-Okollo district. The hand washing in these districts were also low and ranged from 35.5% in Madi-Okollo to 66% in Kasese. The status of WASH in the six districts is shown in Fig. 6.

Figure 6: Status of WASH in the six studied districts of Uganda

Safe water coverage

The study showed that three quarters (75%) of households used the recommended protected water sources. However, 17% of households used surface water sources. In Namayingo district, the majority 63% of the households used surface water or unprotected water sources. The main water sources used by the households in the six districts are shown in the Table 4.

Table 4

The main source of water used by the households in the six study districts of Uganda
Background characteristics	Public taps or stand pipes, % (95%CI)	Boreholes or tube wells, % (95%CI)	Protected spring, % (95%CI)	Protected dug well, % (95%CI)	Surface source (dam, lake, river, stream, pond and canal), % (95%CI)	Unprotected dug well, % (95%CI)	Others, % (95%CI)	Number of households (n)
Overall	39.1 (35.9–42.4)	32.9 (29.8–36.1)	2.7 (1.7–3.9)	2.3 (1.5–3.5)	16.8 (14.4–19.4)	3.4 (2.4–4.9)	2.8 (1.8–4.1)	900
District name
Busia	61.3 (53.0–69.2)	19.3 (13.3–26.6)	12.7 (7.8–19.1)	2.7 (0.1–6.7)	0	0.7 (0.02–3.7)	3.3 (1.1–7.6)	150
Kasese	71.3 (63.4–78.4)	6.7 (3.2–11.9)	0	3.3 (1.1–7.6)	16 (10.5–22.7)	0.7 (0.02–3.7)	2 (0.4–5.7)	150
Madi-Okollo	28 (21.0–35.9)	59.3 (51.0–67.3)	3.3 (1.1–7.6)	0.7 (0.02–3.7)	6.0 (2.8–11.1)	2 (0.4–5.7)	0.7 (0.02–3.7)	150
Namayingo	8.7 (4.7–14.4)	27.3 (20.4–35.2)	0	0.7 (0.02–3.7)	48 (39.8–56.3)	8 (4.2–13.6)	7.3 (3.7–12.7)	150
Ntoroko	38.0 (30.2–46.3)	20 (13.9–27.3)	0	6.7 (3.2–11.9)	26 (19.2–33.8)	9.3 (5.2–15.2)	0	150
Obongi	27.3 (20.4–35.2)	64.7 (56.5–72.3)	0	0	4.7 (1.9–9.4)	0	3.3 (1.1–7.6)	150
Education
None	35.6 (27.3–45.1)	36.4 (28.1–45.9)	2.5 (0.5–7.1)	2.5 (0.5–7.1)	16.1 (9.8–23.6)	4.2 (1.4–9.5)	2.5 (0.5–7.1)	120
Primary	34.2 (30.0–38.7)	36.8 (32.4–41.3)	2.7 (1.5–4.7)	2.5 (1.3–4.4)	17.8 (14.4–21.5)	3.2 (1.8–5.2)	2.7 (1.5–4.7)	473
Secondary	44.7 (38.3–51.3)	26.6 (21.1–32.7)	2.5 (0.9–5.4)	1.7 (0.5–4.3)	17.3 (12.7–22.7)	3.8 (1.8–7.1)	3.4 (1.5–6.5)	237
Post-Secondary	58.6 (46.2–70.2)	21.4 (12.5–32.9)	2.9 (0.3–9.9)	2.9 (0.3–9.9)	10 (4.1–19.5)	2.9 (0.3–9.9)	1.4 (0.0–7.7)	70

Boiling or treating of drinking water

Boiling of drinking water in the all districts was below 50% except Busia (55.3%). Majority of the households (61%) mentioned that they neither boil nor treat drinking water. The findings on boiling or treatment of drinking water are shown in Additional file 3.

Availability of sanitary facilities (Latrines and toilets)

Majority of households (68%) did not have the recommended sanitary facilities (latrines or toilets). More than a third (37%) of the households had no sanitary facilities. The households that had sanitary facilities in the study area are shown in table 5.

Table 5: Percent of households that had a latrine / toilet facility by district and by education level of the household heads
Background characteristics	Has no access to recommended toilet / latrine type (%)	Has access to recommended toilet / latrine type (%)	Ownership of recommended toilet / latrine type					Number of households (n)
Background characteristics	Has no access to recommended toilet / latrine type (%)	Has access to recommended toilet / latrine type (%)	Traditional Pit Latrine (with a washable floor)	VIP Latrine	Ecological sanitation toilet	Pour Flush	Flush Toilet/WC	Number of households (n)
Overall	68.5 (65.4–71.6)	31.5 (28.5–34.7)	23.1 (20.4–26.0)	4.7 (3.4–6.3)	1.6 (0.9–2.6)	1.4 (0.8–2.5)	0.7 (0.2–1.4)	900
District name
Busia	10.7 (6.2–16.7)	89.3 (83.3–93.8)	65.3 (57.1–72.9)	18.0 (12.2–25.1)	0.7 (0.0-3.7)	2.0 (0.4–5.7)	3.3 (1.1–7.6)	150
Kasese	62.6 (54.4–70.4)	37.4 (29.6–45.6)	28.7 (21.6–36.6)	5.3 (2.3–10.2)	0.7 (0.0-3.7)	2.0 (0.4–5.7)	0.7 (0.0-3.7)	150
Madi-Okollo	92.6 (87.3–96.3)	7.4 (3.7–12.7)	2.5 (0.7–6.7)	0.8 (0.0-3.7)	4.1 (1.5–8.5)	0.0	0.0	150
Namayingo	79.7 (72.7–86.1)	20.3 (13.9–27.3)	19.4 (13.3–26.6)	0.9 (0.0-3.7)	0.0	0.0	0.0	150
Ntoroko	92.2 (86.4–95.8)	7.8 (4.2–13.6)	5.0 (2.3–10.2)	0.0	0.0	2.8 (0.7–6.7)	0.0	150
Obongi	84.1 (77.1–89.5)	15.9 (10.5–22.7)	9.8 (5.7–16.0)	0.8 (0.0-3.7)	4.5 (1.9–9.4)	0.8 (0.0-3.7)	0.0	150
Education
None	85.4 (77.9–91.4)	14.6 (8.6–22.1)	8.7 (4.1–15.0)	4.9 (1.9–10,7)	1.0 (0.0-4.6)	0.0	0.0	118
Primary	73.6 (69.4–77.5)	26.4 (22.5–30.6)	19.7 (16.2–23.5)	2.5 (1.3–4.4)	2.2 (1.0-3.9)	1.5 (0.6-3.0)	0.5 (0.0-1.5)	473
Secondary	61.6 (55.1–67.8)	38.4 (32.2–44.9)	29.5 (23.8–35.8)	5.8 (3.3–9.7)	0.9 (0.1-3.0)	1.3 (0.3–3.7)	0.9 (0.1-3.0)	237
Post-Secondary	32.8 (22.1–45.1)	67.2 (54.9–77.9)	44.8 (32.4–56.7)	14.9 (7.1–24.7)	1.5 (0.0-7.7)	3.0 (0.3–9.9)	3.0 (0.3–9.9)	70

There were variations in availability of latrines with education level of the respondents. The higher the education the more likely the respondents were to have the recommended latrines. These differences were statistically significant at each higher education level.

Hand washing after visiting a toilet

Among 802 households that owned sanitary facilities (latrines or toilets), two thirds 66% reported that they always washed hands after using a toilet while 3% never wash hands after using a toilet or latrine. The hand washing practices by districts are shown in Table 6.

Table 6: Percent of respondents that washed hands after visiting the toilet
Background characteristics	Always (%)	Sometimes (%)	Rarely (%)	Never (%)	Number of households (n)
Overall	65.7 (62.3–69.0)	23.3 (20.4–26.4)	8.0 (6.2–10.1)	3.0 (1.9–4.4)	802
District name
Busia	92.7 (87.3–96.3)	7.3 (3.7–12.7)	0.0	0.0	150
Kasese	66.0 (57.8–73.5)	26.0 (19.2–33.8)	6.0 (2.8–11.1)	2.0 (0.4–5.7)	150
Madi-Okollo	35.5 (27.0-44.8)	33.9 (25.5–43.0)	23.1 (16.0-31.7)	7.4 (3.5–13.7)	121
Namayingo	86.1 (78.1–92.0)	13.9 (8.0-21.9)	0.0	0.0	108
Ntoroko	47.5 (39.1–56.1)	37.6 (29.6–46.1)	7.8 (4.0-13.5)	7.1 (3.4–12.7)	141
Obongi	65.2 (56.4–73.2)	21.2 (14.6–21.2)	12.1 (7.1–18.9)	1.5 (0.18–5.4)	132
Education
None	63.1 (53.4–72.7)	22.3 (14.6–31.3)	8.7 (4.0-15.8)	5.8 (2.1–12.1)	104
Primary	61.4 (56.5–66.2)	24.8 (20.7–29.3)	10.6 (7.8–14.0)	3.2 (1.7–5.4)	407
Secondary	71.9 (65.5–77.7)	21.4 (16.2–27.4)	4.9 (2.5–8.6)	1.8 (0.5–4.5)	224
Post-Secondary	76.1 (64.1–85.7)	20.9 (11.9–32.6)	1.5 (0.0–8.0)	1.5 (0.0–8.0)	67

There were differences in hand washing practices between districts and with the education levels of the respondents. However, these differences between the education levels were not statistically significant.

The study found a high vaccination coverage for OCV for both the first and the second dose campaign in all the six study districts. For the first OCV dose, all districts achieved the coverage of above 79%. The second dose average coverage was lower than the first dose at 67%. Ntoroko district recorded the least second dose coverage of 55% which was still higher than the 50% that is required for the community to acquire hard immunity against cholera [40]. The vaccination coverage for COVID-19 vaccines in the same communities were however, lower than for OCV coverages. The vaccine coverage of COVID-19 second dose was on average 18% which is far below the United Nations recommended level of 70% vaccination coverage of the vulnerable persons [44]. This very low COVID-19 vaccination coverage could be attributed to a number of factors.

First, the mass vaccination campaign strategy employed to administer the COVID-19 vaccines that was fixed posts (either at health facility level or outreach post) created accessibility challenges as opposed to the mobile house-to-house mass vaccination strategy that was used for OCV. In addition, since most of the individuals in the study area walked on foot to reach the fixed points, it is possible that the elderly, persons with walking disabilities and are weak, and those with other urgent commitments and businesses opted-out. In this case, to scale-up COVID-19 vaccine uptake, use of a mobile strategy could be explored. This is necessary since increasing the COVID-19 vaccine coverage is important to protect the communities against the evolving COVID-19 global threat [58]. However, there is financial implication for adapting mobile strategy for COVID-19 mass vaccination campaigns. It should be noted that cholera pandemic in Uganda occur in particular locations, hotspot districts and communities [47, 59] and not the whole country as is the case with COVID-19 [35]. Therefore, for COVID-19 vaccination to be conducted by use of mobile strategy, additional operational funds are needed. Getting these extra funds may not be easy following the effects of COVID-19 on the economies [60]. Hence other alternative cost-effective approaches have to be considered including integration of COVID-19 vaccines into the already existing routine immunization strategy.

Secondly, the commonest reason given by the respondents who missed COVID-19 vaccination was fear of the vaccine side effects. Indeed, many respondents in this study reported moderate and some with severe AEFI after COVID-19 vaccines. Similarly, studies in other countries have documented AEFI with COVID-19 vaccines [50, 61, 62]. Consequently, this could have resulted in COVID-19 vaccine hesitancy as previously documented elsewhere in Africa [18, 63, 64]. Hence, further specific studies are required to get better understanding of the COVID-19 vaccines. Interestingly, there were no severe AEFI reported among the OCV recipients in all the studied districts. This findings are in agreement with that of other study which also reported no severe AEFI following mass OCV campaigns [65].

Thirdly, unavailability of COVID-19 vaccines at the health posts could be a limiting factor leading to low coverage since it is a well-documented fact that countries in Africa have difficulties in acquiring the needed vaccines due inequity in COVID-19 vaccine access as a consequence of the vaccine manufacturers prioritizing their own countries and people in the developed nations [66]. We think that Uganda is not unique and could be affected as well. Therefore, ensuring availability of vaccines at the fixed posts, in Uganda and Africa at large is important for COVID-19 prevention. In this regard steps by the Africa Centers for Disease Control (CDC) to promote COVID-19 vaccine production / manufacture of vaccines in Africa [67] should be supported. Meanwhile, there is a need for the implementers in Uganda to incorporate trust building measures during community mobilization and engagements to attract more people to be vaccinated. In addition, in order to get deeper understanding of the factors responsible for the low uptake of COVID-19 vaccines, further studies that involve interviews with key informants and groups in the communities are recommended.

The sustained promotion of safe WASH and waste management practices in the communities and in the public places serve as important interventions in control of transmission and spread of several infectious disease such as the COVID-19 and cholera [68]. However, often after OCV campaigns, vaccine coverage surveys are done [45, 54] but they omit assessing for WASH status which if adequate is an important pillar for healthy living [51]. In this study we incorporated WASH assessments into OCV coverage survey to generate more enriched data for long term cholera preventive planning and for addressing immediate WASH gaps. Previously, there were attempts to collect WASH data during coverage surveys [69]. However, the data collected were not adequate for all WASH. The study revealed suboptimal WASH coverages. For example, the latrine and/or toilet coverages in the five districts of Obongi, Madio-Okollo, Namayingo and Kasese were between 7.4% − 37.4% implying that a significant percentage (62.6% − 92.6%) of the populations in these districts had no access to the recommended sanitary facilities and were practicing open defecation. Therefore, to consolidate the benefits of OCV and to ensure access to safe WASH in line with Sustainable Development Goal (SDG 6) [70], special efforts are needed to promote WASH in the five study districts.

Additionally, since the protection with OCV is for about three years [71] and improvement in WASH takes a long time than the protective period for OCV, there is a need for the future follow up vaccination campaigns to consolidate the preventive achievements. Hence, this study could be a suitable reference document to support future OCV applications from Uganda to Global Task Force for Cholera Control. Besides, this study findings on WASH in communities could be used by stakeholder to assess progress toward ensuring universal access to safe water and sanitation by 2030 as per United Nations’ Sustainable Development Goal 6 [70].

Strength and limitations of this study

To our knowledge, this is the first study to comprehensively incorporate WASH assessment and COVID-19 vaccine coverage into OCV coverage survey. This is important since the data generated allow the actors to simultaneously acquire appropriate planning data to guide prevention of the two ongoing major pandemics in Uganda with a common origin in Asia Despite these strengths, there were also a number of limitations. The data on AEFI were reported by the heads of the households two months after the campaigns. It is possible that some of the mild events were forgotten. However, we think that since during the campaigns the health workers emphasized to the community to notice and report AEFI, the effect of these on our findings was minimal to affect the final conclusion. In regards to the relationship of education level and OCV utilization, respondents with education had higher odds of receiving OCV than those without. Consequently, the respondents with primary education were one and a half times more likely to receive OCV than those without education. However, the odds of receiving OCV though high for both secondary and post-secondary levels than with no education reduced with increasing education levels. We could not explain why there was this reduction in Odds Ratio with education levels. Hence, further studies are required to provide more information.

Lastly, although the coverages for OCV were high for both doses (one and two), we could not explain the high vaccine dropout rate of more than 10% between the doses since in both instances house-to–house vaccine delivery strategy which ensure finding the recipient at their residence was used. Thus, additional studies are need to identify factors that could have resulted in this high dropout rate.

Also, we could not fully explain why Busia district was a cholera hotspot yet it had good WASH coverage. It is a known fact that availability of WASH infrastructure and use are two different things [72]. Furthermore, being a border district it is possible that cross-border activities are at play for frequent cholera outbreaks as documented elsewhere [73]. However, there is no specific literature to support these thoughts. Hence, more studies are needed to provide information on utilization of WASH services.

This study showed that significant efforts had been made in the study area of Uganda to prevent cholera and COVID-19 pandemics by use of measures that included mass vaccination campaigns with appropriate vaccines. While the vaccine coverage for OCV was high, and above the recommended protective level, the one for COVID-19 was low indicating vaccine hesitancy by the community to COVID-19 vaccination. Additionally, there were no severe cases of AEFI recorded with OCV. However, one (1) severe AEFI with COVID-19 vaccine was recorded. Hence further studies are required to provide more information about COVID-19 vaccine AEFI. In regards to the WASH, the study showed that it was feasible to integrate WASH assessment tool (Additional file 1) in cholera coverage survey to generate more data that could be used for long-term cholera prevention and for monitoring of progress toward achievement of some SDGs [70]. Therefore, the WASH assessment tool (Additional file 1) used in this study could be adapted and incorporated in the for OCV surveys in similar settings.

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AEFI Adverse Events Following Immunization

COVID-19 Coronavirus Disease, 2019

OCV Oral Cholera Vaccine

SDG Sustainable Development Goals

UNICEF United Nations Children’s Emergency Fund

WASH Water, Sanitation and Hygiene

WHO World Health Organization

Ethics approval and consent to participate

This study was approved by Makerere University Research and Ethical Committee (SPHREC), study reference No. SPH-2021-179. In order for the respondent to participate in the survey, written informed consent was sought from them or appropriate guardians.

Consent for publication

All respondent consented to publication of these study findings

Availability of data and materials

The datasets generated and/or analyzed during the current study are not publicly available due sensitivity of the medical information therein and but are available from the corresponding author on reasonable request after relevant ethical clearance.

Competing interests

Godfrey Bwire is an Editorial Board Member of BMC Medicine, a peer-reviewed medical journal. None of those research funding is related to this work. All other authors have no competing interests to declare.

Funding

This study was funded by the World Health Organization, Kampala, Uganda, Country office.

Authors' contributions

GB, AK, JNB, JBB and CGO conceived the idea. GB, AK, EA, JBB, JNB, CA, BDN, AO, SA, CGO, collected the data. JBB, JB and GB did the analysis and prepared the figures and tables. GB, AK, EA, JBB, JNB, CA, BDN, AO, SA, CGO wrote the initial draft. GB, AK, EA, JBB, JNB, CA, BDN, AO, SA, CGO, reviewed the draft. GB, AK, EA, JBB, JNB, CA, BDN, AO, SA, CGO read and approved the final manuscript.

Acknowledgements

The authors are grateful to the following organizations: the Ministry of Health, for permission to conduct the study; the WHO, for the technical guidance and funding the study; the six local governments and the communities of Busia, Kasese, Madi Okollo, Obongi, Namayingo and Ntoroko district for participating in the study. The authors in very special way thank the following persons and the research assistants for the wonderful job done in supporting this work and in the collection the data, namely; Ms. Hanifa Bukirwa (administrator) and the research assistants, Additional file 4. Furthermore, the authors are extremely grateful to the district leadership of the six study districts and the respondents for the support and participation in the survey respectively.

Authors' information (optional)

Additionalfile1.pdf
Additional file 1: WASH assessment tool.
Additionalfile2.jpg
Additional file 2: The sources of information on COVID-19.
Additionalfile3.pdf
Additional file 3: Percent of households that boiled or treated the water for drinking by district and educational level.
Additionalfile4.pdf
Additional file 4: List of the research assistants who participated in data collection.

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Journal Publication

published 21 Jul, 2023

Read the published version in BMC Infectious Diseases →

Editorial decision: Major revision
14 Mar, 2023
Reviewers agreed at journal
29 Dec, 2022
Reviewers invited by journal
04 Oct, 2022
Editor invited by journal
21 Sep, 2022
Editor assigned by journal
26 Aug, 2022
First submitted to journal
25 Aug, 2022

You are reading this latest preprint version

Prevention of cholera and COVID-19 pandemics in Uganda: understanding vaccine coverage survey Plus

Status:

Journal Publication

Version 1

Abstract

Background

Methods

Results

Conclusion

Figures

Background

Methods

Study setting

Sample size determination

Selection of the villages and respondents

Study variables

Categorization of Adverse Effects Following Immunization (AEFI)

Data management and analysis

Quality assurance

Results

Demographic characteristics of the respondents

Oral cholera and COVID-19 vaccine coverages

Oral Cholera Vaccine Coverage

Level of awareness about the OCV campaign and knowledge on the benefits of OCV

Barriers to uptake of Oral cholera vaccine

Determinants for the uptake of the Oral Cholera Vaccine

COVID-19 vaccine coverage

Level of awareness about the COVID-19 vaccination, treatment and benefits

Barriers to uptake of COVID-19 vaccines

Distance to the nearest facility

Vaccine Adverse Events following Immunizations (AEFI)

Oral cholera vaccine

COVID-19 Vaccines

Water, sanitation and hygiene coverages

Safe water coverage

Boiling or treating of drinking water

Availability of sanitary facilities (Latrines and toilets)

Hand washing after visiting a toilet

Discussion

Strength and limitations of this study

Conclusion

References

Abbreviations

Declarations

Supplementary Files

Status:

Journal Publication

Version 1