Determinants of measles outbreak in the city of Kinshasa, Democratic Republic of the Congo in 2022: A case-control study

Fabrice Sewolo Matondo^1,&, Jean Okitawutshu Djemba², Antoinette Tshefu Kitoto², Col Gomba Ebbi³, Gauthier Mubenga Mashimba⁴, Ken Kayembe Mabika⁴, Linda Matadi Basadia⁴, Alain Nzanzu Magazani⁴, Leopold Lubula Mulumbu⁵, Annie Iko Abikaa⁶

 

¹Department of Epidemiology and Biostatistics, Kinshasa School of Public Health, University of Kinshasa, Kinshasa, Democratic Republic of Congo, ²Department of Community Health, Kinshasa School of Public Health, University of Kinshasa, Kinshasa, Democratic Republic of Congo, ³Military hospital for veterans, Ministry of National Defense, Kinshasa, Democratic Republic of Congo, ⁴AFENET coordination office, Kinshasa, Democratic Republic of Congo, ⁵Epidemiological Surveillance Directorate, Kinshasa, Democratic Republic of Congo, ⁶Kinshasa Provincial Health Division, Kinshasa, Democratic Republic of Congo

 

 

^&Corresponding author
Fabrice Matondo Sewolo, Department of Epidemiology and Biostatistics, Kinshasa School of Public Health, University of Kinshasa, Kinshasa, Democratic Republic of Congo

 

 

 

 

Despite the existence of a safe and effective vaccine, measles remains one of the leading causes of death in young children worldwide [1].

 

Measles infection is one of the deadliest eruptive diseases with 700,000 deaths per year worldwide [2]. Globally, reported measles cases more than doubled between 2017 and 2018 from 170,000 to 350,000 [3,4]. This upward trend continued in 2019 and several countries experienced significant measles outbreaks with a recent report from the World Health Organization (WHO) showing a 79% increase in the number of measles cases worldwide in the first two months of 2022 compared to the same period in 2021 [5]. In April 2022, nearly 21 major measles outbreaks have been recorded over the past 12 months with adverse effects in Africa and Eastern Mediterranean, the two most affected regions [6].

 

In the Democratic Republic of Congo (DRC), there has been a resurgence of measles epidemics since 2010 [7]. The deadliest was that of 2019 with 6,045 deaths out of 311,471 cases (Case Fatality Rate-CFR 1.9%) compared to that of 2021 where 783 deaths were recorded out of 55,771 cases (CFR 1.4%) [7]. The extent of the epidemic in week 48 of 2022 showed 26/26 provinces affected, which included 212 epidemic- confirmed health zones (HZ) with a cumulative number of 137,057 suspected cases including 1,706 deaths (CFR 1.2%) [8].

 

In 2022, the city of Kinshasa experienced a measles outbreak. The alert was issued in week 2 by the central office of the Kimbanseke Health Zone where 6 cases were confirmed. From epidemiological week (EW) 1 to EW 54 of 2022, 14 Heath Zones experienced a measles outbreak. In total, more than 1,272 cases were reported including 2 deaths (CFR 0.2%) [8].

 

Despite the immunization efforts made over the last five years, there is a persistent 20-point gap between administrative coverage and the annual estimates from WHO and UNICEF (Figure 1). The complexity and multiplicity of factors that influence health condition as well as their socioeconomic aspect deserve to be mainstreamed into strategies to achieve the elimination of measles by 2030 [3].

 

In order to explore the above complexity, three research hypotheses were generated: (1) the low socioeconomic level of households is associated with measles outbreak, (2) the parents' low level of knowledge about measles prevention is associated with the occurrence of the measles epidemic, and (3) the lack of childhood vaccination is associated with measles outbreak.

 

Given that information on the resurgence of measles serves as a marker of health system weaknesses and persistent inequalities in access to care, measles elimination and control activities therefore, play an important role in strengthening immunization programs and in contributing to primary health care [9]. This study determined the factors that could explain measles outbreak in the city of Kinshasa.

 

 

Study design

 

This was an unmatched case-control study conducted among children aged 6 months to 15 years inclusive living in measles epidemic HZ in Kinshasa city, DRC.

 

Case definition and finding

 

The WHO definitions were adopted to identify suspect cases, probable cases of measles with an epidemiological link and confirmed cases [9]. A confirmed case was a suspected case that was confirmed Immunoglobulin M (IgM) serology positive in a laboratory. For this study, only laboratory-confirmed cases were included. Controls were close neighbors not affected by measles aged 6 months to 15 years inclusive. Additionally, parents/guardians of cases and controls were interviewed.

 

Sample size

 

The sample size was calculated by Open source Epidemiologic Calculator, OpenEpi version 7 using the following parameters: Proportion of unvaccinated among controls of 17% with an odds ratio (OR) of 2.55, significance threshold of 5%, power of 80%, case-control ratio of 1:1, all at 95% confidence interval [10]. This resulted in a sample of 384 subjects. Accounting for the correction factor of 10% non-responses, the estimated sample was 422, which was ultimately increased to 500, i.e. 250 cases and 250 controls.

 

Sampling technique

 

A cluster-random sampling of cases was applied. The 14 HZ that had a confirmed epidemic in 2022 were classified according to whether they belonged to the Expanded Program of Immunization (EPI) branches (referred to as cluster) of the Kinshasa Provincial Health: (1) Kin-Est Branch, (2) Kin-centre Branch, and (3) Kin-Ouest Branch. HZ were sorted in alphabetical order and numbered within each EPI branch. The weight of each EPI branch was computed and 8 HZ were randomly selected proportionally (1) Kin-Est Branch 8 x 8/14 = 5 (Biyela, Kimbanseke, Kingasani, Masina I and Ndjili); (2) Kin-Centre Branch 4 x 8/14 = 2 (Limete and Kasavubu); (3) Kin-Ouest Branch: 2 x 8/14 = 1 (Kokolo).

 

A proportional allocation of statistical units in the 8 selected HZ was carried out to determine the sample share for each EPI branch. The distribution of the sample with regard to the number of cases reported in the 8 selected HZ is shown in Figure 2.

 

each selected HZ, the statistical units were sorted in alphabetical order from the line list and randomly selected using the Open Epi software. The subjects selected were sought out in the community and subsequently interviewed. Controls were recruited from among their close neighbors, in the plot to the left or right of the case household.

 

Study outcomes

 

The primary outcome of this study was measles case coded yes and no. Exposure variables were the mother's level of education, mother's age, occupation of the head of household, religion, household size, marital status of parents, antenatal consultation visits attendance, parent´s level of knowledge of measles, household´s socioeconomic status (SES) expressed as wealth quintiles, housing type, child´s age, child´s sex, close living, notion of contact, child´s immunization status, number of people sharing a bedroom.

 

The parent´s knowledge of measles was scored. Closed and semi-open questions expressing the parents' level of knowledge of the symptoms and prevention of measles was collected. For each correct or incorrect answer, a score of 1 or 0 was assigned respectively. The total knowledge score was calculated, expressed in proportions stratified in: 1) High level (≥0.75); 2) Average level (0.50-0.74), and 3) Low level (<0.50).

 

Data collection

 

The data was collected from two sources. First, the line list of the Kinshasa provincial health division and that of the selected HZs from which information including health area, address, epidemiological week, age, sex, disease status (laboratory confirmation or epidemiological link) were collected. Second, a community-based household survey was conducted by trained data collectors through face-to-face interviews using a structured electronic questionnaire programmed as Kobo forms on Android devices. Constraints were introduced into the questionnaire to minimize as much as possible errors that could affect the quality of the data. The questionnaire was translated into the local language (Lingala), to make it more understandable for the interviewees.

 

Data analysis

 

The data was downloaded from a secure server as Comma-separated values (CSV) datasets, cleaned and analyzed in Stata SE/v. Quantitative data were expressed as medians and interquartile range (IQR). Mean were compared using the unpaired t-test or the Wilcoxon rank sum test when the t-test validity criteria were not met. Categorical data were summarized as proportions with their 95% confidence intervals (95% CI), they were compared using Pearson's chi-square test or Fisher's exact test. A p-value less than 0.05 was considered statistically significant. Crude odds ratios (COR) with their 95% CI were computed before setting up the final logistic regression model. A p-value less than or equal to 0.20 was the criterion used to select variables for multivariate logistic regression. Multicollinearity was checked among the selected independent variables via the variance inflation factor (VIF). The p-value less than 0.05 was considered statistically significant in the final model. The quality adequacy of the final model was checked using the Hosmer and Lemeshow test and was found to be suitable. Adjusted odds ratio (aOR) with their corresponding 95% confidence intervals were used to illustrate the strength of the association between independent factors and measles.

 

Ethical consideration

 

The County of the Kinshasa Provincial Health Team granted permission to use the data from the outbreak response for this study and its publication. Confidentiality of the participants was maintained throughout the study. A written informed consent was obtained from parents/legal guardians of all child participants prior to starting interviews. Participation in this study was voluntary. Likewise, the confidentiality of the data collected and the freedom for participants to withdraw from the study at any time point were guaranteed. No biological procedures were involved during the collection and processing of the data.

 

 

Characteristics of study participants

 

Table 1 summarizes the characteristics of children sampled. Overall, 500 subjects were included in the study (250 cases and 250 controls). The median (IQR) age was 4 (2-7) years for cases and 3 (1-5) years for controls. The proportion of children aged 1 to 4 years was greater in the control group compared to the cases (p<0.001). The distribution of sex in both groups was homogeneous (p=0.179) while that of vaccination status was not (p<0.001) (Table 1). The number of people sharing a bedroom in both groups was not significantly different (p= 0.070). Nearly 7 out of 10 cases (69.2%) had been in contact with a sick child compared to 39.2% among controls (p<0.001).

 

Table 2 displays characteristics of respondents and households. Most of the mothers were within the 20 - 30 years age group (cases, 60.0%; controls, 56.4%). The proportion of guardians with secondary education was higher among cases (62.8%) compared to controls (42.0%). Overall, the professions of household heads were homogeneous in the two groups (p= 0.466). More than half of the households among cases belonged to the revival church compared to the controls (55.2% vs. 28.4%). In both groups, the majority of respondents were mothers (case, 84.4%; controls79.6%). The marital status in both groups was not homogeneous (p=<0.001). The proportion of mothers who correctly followed ANC was higher in controls compared to cases (62% vs 41.6%). Likewise, the proportion of households with less than 6 people was significantly higher among controls compared to cases (65.2% vs 51.2%). The type of residence was homogeneous in both groups (p=0.443). Level of knowledge of measles prevention was low in almost half of the guardians in both groups.

 

With regard to socioeconomic status, the cases seemed significantly poorest compared to controls (26% vs. 14%), p = 0.003 (Table 3). Half of the cases were unvaccinated (50.4%) and were significantly more likely to develop measles compared to controls (cOR: 2.04 95% CI: 1.41 - 2.95). Children of older mothers (20 years and above) were less likely to develop measles compared to children of younger mothers as a reference. Compared to children of illiterate mothers, those of mothers with primary education were less susceptible to measles (cOR: 0.26 95% CI: 0.12-0.56). On the other hand, children of Christian mothers were significantly more likely to develop measles (cOR: 2.94 95% CI: 1.96 - 4.42) compared to those of non-Christians. Susceptibility to measles was also significantly associated with the household size (cOR: 1.8 95% CI 1.2 - 2.5) and close living (cOR: 2.22 95% CI 1.46 - 3.39). Likewise, the marital status of the child's guardian (married) was shown to be positively associated with measles (cOR: 1.5 95% CI 1.05 - 2.27). Conversely, a high socioeconomic index seemed a significant protective factor against measles (cOR: 0.6 95% CI 0.3 - 0.9). Children aged 1 to 4 years were less likely to develop measles compared to those under 1 year (cOR:0.36 95%CI: 0.17-0.77). On the other hand, close living was significantly associated with the occurrence of measles (OR: 2.16 95% CI: 1.36 - 3.4), and lack of contact with a measles case was protective against measles (OR: 0.29 95% CI: 0.19 - 0.42).

 

After adjusting for confounders in a multivariate logistic regression model, eight variables were significantly associated with measles: mother's age, education, religion, child´s age, immunization status, close living (proximity), contact with measles case, and SES. Susceptibility to measles infection was lower among children of mothers aged 20 - 30 years (aOR: 0.07 95% CI 0.01 - 0.32) and those over 30 (aOR: 0.05 95% CI 0.10 - 0.21) compared to those of younger mothers. The susceptibility of measles occurrence was 4 times less observed in cases of mothers with Primary education (aOR: 0.23 95% CI 0.09 - 0.60) than in children of illiterate mothers. It was 3 times higher among children of Christians (aOR 3.2 96% CI: 1.82 - 5.02) compared to children of non-Christians (Table 4). The susceptibility of developing measles was 76% less observed in children aged 1 to 4 years than in children under 1 (aOR 0.24 96% CI: 0.09 - 0.62). Unvaccinated children were 3 times more likely to develop measles compared to the vaccinated (aOR: 3.17 95% CI: 1.93 - 5.21). Children in very close living were almost 3 times more likely to develop measles compared to those in less close living (aOR: 2.73 95% CI 1.29 - 5.73). The lack of contact with a measles case was a protective factor against measles (aOR: 0.22 95% CI: 0.13 - 0.36). Likewise, children from households with high wealth index were 74% less susceptible to measles infection compared to those from households with a poor wealth index (aOR: 0.26 95% CI: 0.14 - 0 .48).

 

 

This study confirmed the hypotheses previously set out. It highlighted the determinants of measles outbreaks in the city of Kinshasa which are: young age of the mother, illiteracy of parents, Christian religion, children aged 1 to 4 years old, the absence of vaccination, high promiscuity, contact history and low socio-economic index in Kinshasa.

 

Measles infection was higher among children of young mothers. This corroborates with findings by Carlito et al. [11], probably due in part to the mother's lack of experience and her ignorance of the disease as well as prevention measures. However, this conclusion differs from that found in Ethiopia [12]. A significant proportion of measles cases were found in children whose parents were not educated. In fact, illiteracy is one of the major challenges hampering the control of measles in the DRC. Barriers to women's access to education constitute a primary factor that must be addressed urgently by any health policy. This corroborates conclusions from a survey carried out as part of a health development project in Benin [13]. Indeed, this study highlighted the relationship between women´s education level and the poor use of health services. Consequently, the lower the level of education, the lower the use of health services [13]. Studies show that education can transform the behavior, attitudes and practices of spouses for better use of modern preventive and curative methods and women's autonomy [14,15]. Additionally, the incidence of measles was found to be higher in households where the mother had no education [16].On the other hand, tutors with a higher level of education often have better access to information, including online sources. However, this can also expose them to misinformation or conspiracy theories about vaccines. Overabundance of contradictory information can sow doubt and mistrust. They may have higher expectations of transparency and communication from health authorities. If these expectations are not met, this can lead to a loss of trust and a reluctance to follow vaccine recommendations. Individuals with a higher level of education may feel more autonomous and competent to make decisions about their children's health. They may be more inclined to question medical recommendations and seek alternatives.

 

In this study, half of the cases were not vaccinated (50.4%). Previous measles vaccination coverage showed an inverse association with measles outbreak, suggesting a protective effect. The association between measles occurrence and the absence of vaccination is well documented by numerous studies [17-20].

 

The protective role of vaccination in the measles outbreak was demonstrated in a study conducted in Aweil East County, South Sudan [21], similar observation was documented by María F et al. in Ecuador [19]. A study conducted in Burkina Faso to determine risk factors for measles outbreak and estimate vaccine effectiveness showed that lack of vaccination was the main risk factor for measles and poor performance of measles vaccine does not appear to be a major cause of the epidemic [20]. Although the WHO AFRO strategy to eliminate measles calls for maintaining vaccination coverage above 95% through high-quality routine vaccination services at national, intermediate and peripheral levels [3], the complete vaccination coverage rate in the DRC is still low. The last vaccination coverage survey 2021 recorded a complete basic vaccination coverage rate of 42% (1.8 million), with 45% of children under immunized (1.7 million) and 13% of “zero dose” (0.5million), i.e. in 2021, one in eight children had not received any vaccine, while one in two children had not received all their vaccines; under immunized children are 3.3 times more numerous than unvaccinated children [22]. Based on administrative data, coverage has remained unchanged over the last 5 years and there is a persistent 20-point gap between administrative coverage and WHO-UNICEF annual estimates.

 

In the city of Kinshasa, administrative vaccination coverage was 85% in 2022 while it was only 65.5% according to vaccination coverage surveys [22]. The average vaccination coverage over the past five years was 86%, well below the 95% immunity level needed to stop measles transmission in an endemic community.

 

However, the occurrence of measles in the 124 vaccinated participants in this study raises the issue of seroconversion [23]. A study carried out in 2014 in Nigeria found a seroconversion profile of 68.6% after a vaccination campaign in suburban areas. This could be due to the low potency of the vaccine with titers between log10-1.0 and log10-2.25 TCID/per dose [24]. The failure of seroconversion in 32.4% of these children was in part attributed to the administration of under-potent vaccines, as evidenced by the measles vaccine potency test result [24]. Immunity acquired by measles vaccination appears to be a continuum ranging from total and lasting protection to a minimal or no protection, including partial or temporary protection [25].

 

In this study, children aged 1 - 4 years were less likely to develop measles compared to the youngest. This finding is consistent with evidence from Ghana where children aged 6 - 9 months and 9 - 11 months were the most affected by measles [16], unlike findings from Katanga Province in 2012, where 1-4 years showed greater susceptibility [26].

 

However, measles infection before 9 months remains a major concern in developing countries [19,10], highlighting the low titers of non-protective antibodies by the time they are due for measles vaccination (9 months), suggesting that younger than 9 months are poorly protected against measles [24,27]. Hence the need to adapt the routine vaccination schedule and contextualize it to the susceptibility of under 9 months.

 

Among the environmental and anamnestic characteristics, very close living and contact with a measles case were found to be risk factors in this study similar to findings from a case-control study done in Ethiopia [28]. Measles is a highly contagious disease, and its transmission is precipitated by close living and contact with measles cases. When several children sleep together, the risk of intense exposure is obviously much greater. This finding is consistent with findings from Ethiopia and Ecuador [ 17,19]. The practice of close living and its association with measles can be explained by economic and demographic factors, but also by African social practices which do not always allow isolating of the sick. In addition, cordiality and good neighborly relationships encourage visits which are opportunities to contract the disease through direct contact or to spread it.

 

Regarding religious beliefs, this study demonstrated a significant association between being Christian and measles. This contrasts with findings from Burkina Faso, where Muslim religion was a risk factor independently associated with measles [20]. The difference observed between our study in the Democratic Republic of Congo (DRC) and that in Burkina Faso can be attributed to several contextual and socio-cultural factors that influence the dynamics of measles transmission in these two regions especially religious and community practices. In the DRC, Christianity represents approximately 90% of the population and certain Christian communities, particularly in the areas studied in Kinshasa, regularly organize major religious gatherings, such as Sunday services, prayer meetings and other community events. These gatherings, often well attended and with few infection control measures in place, can facilitate measles transmission, especially in contexts of low vaccination coverage.

 

In this study, the low SES, resulting in poverty and close living was significantly associated with an increased likelihood of being a measles case, highlighting the potential impact of socioeconomic factors on disease transmission. Guillaume Agnès demonstrated that the socio-economic environment of populations constitutes an important determinant of the health status of a community [29]. Numerous studies have shown that housing conditions can expose children to risks of morbidity and mortality [14,15].

 

Study limitations

 

This study had some limitations of observational study design. Many cases were confirmed by epidemiological link rather than laboratory confirmation. The vaccination status of many cases was confirmed by simple declaration of parents/ guardians given the low possession/ availability of vaccination cards, especially in older children that could lead to classification bias.

 

Also, retrospective interviews are subject to memory bias. Efforts were made to minimize this bias, by restricting the duration to 1 year resulting in the recruitment of cases that only occurred in 2022. The possible impact of confounding factors on the association between potential risk factors and measles occurrence was mitigated by the multivariate analysis. However, some variables such as Vitamin A supplementation known to be related to measles were not included into the model because that data was not collected.

 

 

Despite the above limitations, this study highlighted the determinants of measles outbreaks in the city of Kinshasa which are: young age of the mother, illiteracy of parents, christian religion, age of the child from 1 to 4 years old, the absence of vaccination, living in close proximity with a case, contact history and low socio-economic index. in Kinshasa. Given these findings, a persistently low rate of routine vaccination coverage is the most critical factor in the measles epidemic in Kinshasa. Consequently, improving vaccination coverage by strengthening routine vaccination activities, adjusting the VAR vaccination schedule through a booster dose at 15 months of age, and taking into account of the susceptibility of under nine months to measles is of high value. This raises the following question “hen the VAR should be initiated given the fact that measles occurs in children under 9 months?” Intensifying awareness-raising activities as well as community risk communication remain essential measures to prevent measles cases. This study also highlighted the need to improve maternal education and household’s socio-economic level to prevent measles outbreaks.

 

 

 

 

The authors declare no competing interests.

 

 

FSM, JOD and ATK, conceptualized and designed the study and wrote the protocol. JOD, ATK, GMM, KKM, LMB, AIM and ANM, revised its draft versions. FSM, and GEB coordinated the fieldwork. FSM and AIM contributed to the care and management of the data. FSM analyzed the data and prepared figures. JOD, ATK, and FSM contributed to the interpretation of the results. FSM wrote the first draft of the manuscript. All authors agree with the recommendations of this work. All authors have read and approved the final version of the submitted paper.

 

 

The authors would like to express their sincere thanks to the children and their caregivers who agreed to participate in this survey, to the health authorities of the Kinshasa Provincial Health Division, as well as to the field team who collected the data. Special thanks should be given to Sylvie Mpangi (Provincial Health Division, DRC) for her contribution to important aspects of this work.

 

 

Table 1: Characteristics of children recruited in the City of Kinshasa, 2022

Table 2: Characteristics of recruited guardians and households in the city of Kinshasa, 2022

Table 3: Households socio-economic status in the City of Kinshasa, 2022

Table 4: Determinants of measles outbreaks in the city of Kinshasa, 2022

Figure 1: Administrative coverage versus annual estimates from immunization coverage surveys in the city of Kinshasa from 2017 to 2021

Figure 2: Spatial distribution of health zones in measles epidemic sampled in the city of Kinshasa from SE to SE52 2022

 

 

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