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Introduction Health service use among the public can decline during outbreaks and had been predicted among low and middle-income countries during the COVID-19 pandemic. In March 2020, the government of the Democratic Republic of the Congo (DRC) started implementing public health measures across Kinshasa, including strict lockdown measures in the Gombe health zone. Methods Using monthly time series data from the DRC Health Management Information System (January 2018 to December 2020) and interrupted time series with mixed effects segmented Poisson regression models, we evaluated the impact of the pandemic on the use of essential health services (outpatient visits, maternal health, vaccinations, visits for common infectious diseases and non-communicable diseases) during the first wave of the pandemic in Kinshasa. Analyses were stratified by age, sex, health facility and lockdown policy (ie, Gombe vs other health zones). Results Health service use dropped rapidly following the start of the pandemic and ranged from 16% for visits for hypertension to 39% for visits for diabetes. However, reductions were highly concentrated in Gombe (81% decline in outpatient visits) relative to other health zones. When the lockdown was lifted, total visits and visits for infectious diseases and non-communicable diseases increased approximately twofold. Hospitals were more affected than health centres. Overall, the use of maternal health services and vaccinations was not significantly affected. Conclusion The COVID-19 pandemic resulted in important reductions in health service utilisation in Kinshasa, particularly Gombe. Lifting of lockdown led to a rebound in the level of health service use but it remained lower than prepandemic levels.
With a population of over 14 million, Kinshasa is one of the largest and most densely populated cities in Africa. The DRC health system is organised into health zones, which are further disaggregated into health areas. Each health zone should have at least one hospital, while each health area should have at least one health centre. Currently, Kinshasa has 851 health centres and 121 hospitals—some of which were designated COVID-19 treatment centres (figure 1). The city is subdivided into 24 communes, or municipalities, including Gombe, which is one of the more central and affluent communes. Gombe is a mixed residential and business district. It is also the home to many national and provincial government buildings as well as the Kinshasa Provincial Hospital. There is also an active private sector, which plays an important complementary role in delivering health services.31 A map of Kinshasa with health zones outlined and showing eight health facilities, initially identified as centres for COVID-19 case treatment and hospitalisation (March to April 2020). The map only shows 33 health zones—two health zones (Maluku I and Maluku II) are not shown to optimise visibility. Gombe is highlighted in green. The first case of COVID-19 in the DRC was identified on 10 March 2020.32 The government immediately introduced an outbreak management and control plan including a series of public health measures aimed at reducing transmission of the virus including the closure of bars, restaurants and schools a few days later which was subsequently followed by a declaration of a state of emergency, closing of international borders and restricting travel in and out of Kinshasa on 24 March 2020. On 6 April 2020, the commune of Gombe, at the time known as the epicentre of the epidemic, was locked down, which closed stores and restricted all non-essential travel in and out of the commune and limited all movement within the commune to essential travel only. Health facilities and pharmacies remained open during this period and health-related travel was exempted from the lockdown (including for non-residents who were still allowed to enter Gombe to access health services); however, there was no public transportation or taxis available within the commune. Free movement of transportation was allowed in other parts of Kinshasa. The lockdown was partially lifted on 22 April, allowing residents to purchase food and other essentials, but remained in place until 29 June. There was no lockdown outside of the Gombe health zone. Figure 2 provides an overview of the confirmed cases of COVID-19 in Kinshasa and other DRC provinces. Monthly reported confirmed COVID-19 cases in Kinshasa and other Democratic Republic of the Congo (DRC) provinces. We used monthly time series data on service utilisation from the DRC Health Management Information System (HMIS), an electronic data collection system based on the District Health Information System 2 (DHIS2) platform.33 Specifically, we extracted data covering the pre-COVID-19 period (January 2018 to February 2020) and the COVID-19 period (March to December 2020). These data are input from health facilities’ monthly health service use reports at district health offices. Considerable efforts have been made to improve the quality of HMIS data in DRC, including continual quality assessment activities at both the health zone and facility levels and incentives for report submission and completion.33 The data in this system have been used previously by the research team to conduct other evaluation projects.30 Data on COVID-19 cases were obtained from government sources and data on major policy responses were collected using official government sources.2 Our unit of observation was the facility month. Our study sample included health facilities (ie, health centres and hospitals) across Kinshasa that reported consistently through DHIS2 during the study period. Because not all health facilities provide all health services, we used facility reporting patterns in the HMIS database for each service to determine whether a given health facility should be deemed a facility that provides a relevant service. Specifically, a facility had to have reported a service (eg, facility-based childbirth) at least 1 month into the database to be considered as a facility that provides delivery care. Additionally, we included health facilities for each service that had a reporting rate of at least 25% both before COVID-19 and after the onset of the pandemic. Further, facilities with consecutive missing observations and/or outliers for a specific service were excluded from our sample. Because of these inclusion/exclusion criteria, the number of facilities included in our final analytical sample varied by indicator (see online supplemental table 1). Most health centres provide all services we studied; most hospitals provide all services except vaccinations that are not primarily provided at the hospital level (see online supplemental table 1). We excluded health posts, which provide largely health promotion and community health services, and private health facilities because their reporting rates are limited. bmjgh-2021-005955supp001.pdf We evaluated the impact of COVID-19 on 14 indicators of health service utilisation: These indicators were selected because they accounted for the majority of primary care services provided by health facilities as well as those we believed could be influenced by the pandemic (see online supplemental table 2) as well as indicators with relatively high completeness reporting rates, except for the pneumonia and the NCD indicators, which had median reporting rates less than 60% but were still included to provide a more comprehensive picture of health service utilisation. We used interrupted time series (ITS) analyses to assess the impact of the onset of the pandemic and the government response measures, using monthly time series data, while controlling for secular trends in the outcomes.34 35 As March 2020 was partially exposed to the pandemic and was also not exposed to the Gombe lockdown, we excluded it from our analyses by defining the start of both events as April 2020 and the Gombe lockdown period as April to June 2020. As baseline rates in health service volume vary across health facilities, we employed segmented quasi-Poisson mixed effects models, with health facility catchment population as an offset to estimate the impact on each indicator immediately following the start of the pandemic or the Gombe lockdown (level change) and over time (trend change) (see online statistical appendix). All our models were also adjusted for seasonality. Additionally, models for total outpatient visits and visits for common infectious diseases included a dummy variable to adjust for an unrelated pneumonia outbreak that took place in Kinshasa from December 2019 to February 2020. We also provide results from analyses that were not adjusted for the pneumonia outbreak in the online supplemental table 3 as a sensitivity analysis. We defined outliers for each indicator as any observation exceeding seven SDs from the meantime trend estimated using facility-level local regression, which were subsequently treated as missing observations. Missing data were imputed using seasonally decomposed missing value imputation, accounting for seasonal patterns in the service utilisation time series data.36 We also performed sensitivity analyses using complete case analyses—that is, analyses that include facilities that had complete reporting or no missing values during the study period. We run our ITS models on all health zones in Kinshasa to quantify the effect of the pandemic across the city (see Statistical Appendix). We also conducted subgroup analyses. First, wherever possible, we stratified our analyses by the Gombe versus the remaining 34 health zones to estimate the additional impact of the lockdown versus COVID-19 alone. For the Gombe health zone, we also ran models that included segments (level and trend changes) for the lockdown (April to June 2020) and postlockdown (July to December 2020) periods, allowing us to also estimate the impact of stopping the policy (see Statistical Appendix). Second, we conducted additional analyses to investigate whether the pandemic had a differential impact on different groups, specifically we stratified our sample by sex, age and health facility type wherever feasible. We report parameter estimates using the incidence rate ratio (IRR) and related 95% CI. We also present changes visually using monthly time series indicating mean service utilisation per facility. All analyses were conducted using R V.4.0.2. The funder of the study had no role in study design, data collection, data analysis, data interpretation or writing of the report. All authors had full access to all the data in the study and had final responsibility for the decision to submit for publication. This research was done without patient involvement. Patients were not invited to comment on the study design and were not consulted to develop patient-relevant outcomes or interpret the results. Patients were not invited to contribute to the writing or editing of this document for readability or accuracy.
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