Discussion
Our study assessed changes in maternal health service usage, especially ANC and SBA, at the subnational level by comparing pre-COVID-19 and COVID-19 outbreak periods. The results highlight variations in progress in maternal health services usage, specifically in skilled births and ANC services, as recorded in the routinely collected Kenya and Ethiopia HMIS databases. Results from the study show that subnational disparities are mostly masked in national-level analytical studies. This highlights the specific needs of the various counties and regions in Kenya and Ethiopia, respectively, as different areas are moving towards meeting national and global targets, such as the SDGs, at very different paces. Due to the variation of subnational contexts in geography, population density, urbanisation, socioeconomics, climate, policy environments and cultures, we should not expect uniformity in progress across counties, states and regions. Besides, the pandemic has not affected all counties and provinces similarly in terms of cases and deaths due to COVID-19. These subnational areas also vary in their responses and capacities to mitigate the adverse impacts of the pandemic. Thus, this study emphasises the importance of conducting analyses and depicting changes at the subnational level, even when there are no significant changes at the national level.
Unlike deliveries, where women may not have control over the timing of birth, ANC services are primarily preventive. They may be subject to lower usage if women perceive the service as less essential.11 38 39 Our study’s results are consistent with other studies conducted in LMICs. For instance, in India, a decline in the usage of antenatal services was observed, with about 33.5% of pregnant women having fewer ANC visits as compared with the pre-COVID-19 period.4 Women avoided routine antenatal check-ups due to the strict lockdown and delays in reaching a health facility.4 One qualitative study in Kenya reported that limited access to health facilities for antenatal services was due to the fear of pregnant women contracting COVID-19 and the insufficient number of health workers providing such services.18
Furthermore, most women started visiting antenatal clinics very late (sometimes in their sixth or seventh month of pregnancy) and missed necessary vaccinations such as tetanus toxoid; antenatal services among adolescents, including revisiting clients, were also reduced in Kenya.3 Again, other indirect impacts of COVID-19 potentially disrupt skilled deliveries as many women opt for home deliveries and deliveries at nearby non-health facilities due to inaccessibility resulting from lockdown and mobility restrictions, lack of transport and fear of contracting COVID-19 at the health facilities.39 Such practices, however, were not uniformly observed across the continent though. For example, Temesgen et al
40 found no change in Ethiopia, as about 8 out of 10 women had appropriate care during delivery at the health facilities, while more than 81.3% mentioned that COVID-19 had not strengthened the desire for home deliveries.
Besides the fear of contracting COVID-19, which has been suggested as a possibility for people avoiding hospitals and other health facilities, thereby under using health services, several reports have also been given on other fears such as police brutality and demonstrations spurred on by the lockdowns.41 Kenya is no stranger to violence sparked by protests and clashes between the people and law enforcement. In Nyeri, dozens of local vendors clashed in a riot with the police on 6 April 2020, over discontent with government-imposed mandatory COVID-19 business closures. The clashes reportedly occurred in the town centre following Nyeri County administration officials’ refusal to allow the vendors to reopen.42 Also, Kiambu, one of the top 10 counties hit by COVID-19, continued to be under stricter surveillance and restrictions due to COVID-19, along with the likes of Nairobi, Kajiado, Machakos and Nakuru. Indeed, after Nairobi and Mombasa, Kiambu was the third hardest-hit county in Kenya.42
The WHO, United States Agency for International Development and the Kenya Ministry of Health earmarked several counties as high-priority areas for focused maternal health services due to high maternal deaths,43 even before the coronavirus outbreak. Turkana and Marsabit, counties with widening disparities in both ANC and SBA, are among these priority counties that were already underperforming43 before the pandemic hit Kenya. Incidentally, their continued declines in maternal health service usage from 2018 to 2020 could be attributed to or exacerbated by disruptions from the pandemic, while acknowledging existing challenges pre-COVID-19. Turkana, Marsabit and Embu counties consistently have recorded declining rates for ANC and SBA compared with all other counties. Incidentally, these counties are reported to have one of the highest poverty and socioeconomic disparities in Kenya, where more than 60% of people live in poverty, according to the 2015–2016 Kenya Integrated Household Budget Survey. Again, for the mean per-person expenditure (a measure reflecting the cost of living determined by policy and market forces), Turkana ranks among the lowest of the 47 counties in Kenya compared with Nairobi and Mombasa.44 Turkana County presents a unique case when looking at the two indicators of interest. The county is lagging behind all others in making progress towards improving SBA as well as ANC rates for women. This could plausibly trickle down to increasing county maternal and under-five deaths.44 Recently, northern Kenya has been experiencing perennial droughts, potentially further exacerbating this area’s inequalities.
In Ethiopia, the data suggest that COVID-19 has not significantly disrupted the usage of ANC and SBA services. However, when focusing on ANC, the data shows that almost all regions have not progressed, far below SDG targets. Afar, Amhara, Benishangul-Gumuz, SNNP and Gambela’s rates deteriorated during COVID-19. In the remaining regions, rates have remained relatively stable, although below recommended WHO coverage. Over the assessment period from 2016 to 2021, we see that for most regions, sporadic or persisting low levels of ANC usage started in the pre-COVID-19 period and continued during the COVID-19 periods. Surprisingly, despite initial low levels of ANC in Harari, Sidama and Dire-Dawa, there has been a post-COVID-19 increase in usage. The lack of improved ANC attendance can be explained by the fact that ANC services are preventive, and women perceive them as unessential, which may lead to lower usage of the services.11 38 39 In addition, there are many barriers that women in Ethiopia have been reported to face when attempting to access ANC services. For example, difficulty navigating local health systems, the shame of unwanted pregnancy, a lack of partner approval, a lack of transport and high transport costs.45 COVID-19 may have compounded these barriers, but the overall downward trend in ANC usage began before 2020.
Assessing SBA in Ethiopia, we find that when comparing pre-COVID-19 and during COVID-19 rates, five southern regions have experienced significant increases in usage (Somali, Oromia, Sidama, SNNP and Harari), although below recommended WHO coverage. However, Amhara, Benishagul-Gumuz and Dire-Dawa city regions experienced no change between the two periods. Only the Afar region experienced a significant decrease. Looking at trend data, we note that COVID-19 has not deterred women from SBA over time, as rates in most regions are increasing during the COVID-19 period, although below SDG targets and WHO-recommended coverage. The southern regions of Ethiopia are performing better than the northern regions. Our results illustrate the importance of focusing on subnational performance. According to the World Bank’s Ethiopia socioeconomic dashboard,46 the poverty rate is highest in the northern regions of Tigray, Afar, Amhara and Benishangul-Gumuz. These regions of Ethiopia, in particular Tigray, Amhara and Afar, have endured many years of political and social unrest. It is, therefore, reasonable to expect service usage to be affected by this climate. It is somewhat surprising that in Amhara, despite these challenges, the region is experiencing improvement in SBA rates even during COVID-19.
It is reassuring to see that the pandemic has not resulted in rapidly deteriorating ANC and SBA rates and that some regions are either maintaining or improving the usage of these essential services. The counterfactual analysis results corroborate previous studies’ findings; for example, Temesgen et al
40 Although Ethiopia is improving and maternal and neonatal mortality rates are reducing, the changing pace is likely insufficient to attain the SDGs.
In Kenya and Ethiopia, urbanisation has been shown to be a key driver of COVID-19 attacks and death rates. People living in the urban settings of Nairobi, Mombasa, Addis Ababa and Harari, among other cities, experienced higher incidence rates of COVID-19.
Urbanisation in LMICs contributes significantly to overcrowding and poor sanitation; these conditions provide a perfect recipe for spreading infectious diseases such as COVID-19.47 In 2018, the urban population of Ethiopia was estimated to account for 21.2% of its 112 million people, and its urbanisation rate stood at 4.9%. At the onset of the COVID-19 pandemic, governments globally implemented non-pharmaceutical interventions to reduce the spread of COVID-19, including partial or total lockdowns of entire regions or countries. These measures meant that people spent more time at home, many of whom, especially in Africa, were in overcrowded conditions.48 Living in crowded housing conditions makes it harder to self-isolate and shield from COVID-19.
Our study reiterates that the impacts of the pandemic at the individual, societal and government levels have possibly affected the health-seeking behaviours of women in need of maternal health services through fewer services, delays in seeking care, delays in reaching healthcare services and delays in receiving adequate care at a health facility, all of which would subsequently increase and worsen the plight of women in using essential maternal health services.
Putting countries back on track to achieving the SDGs: What can governments do to get back on track to attain maternal health targets? How can lessons learnt from the study inform policies?
Ideally, with efforts being made in the policy environment being strengthened to accelerate the pace towards achieving maternal and child health targets, we expect to observe increasing trends in service usage. Nonetheless, with the unprecedented spread of COVID-19 in Kenya, in addition to already existing barriers to service usage, we can allude that in certain parts of the country, the pandemic has taken its toll and more so in Kiambu, Kajiado, Embu, Turkana, Nairobi, Mombasa, Nyeri and Meru counties. In Kenya and Ethiopia, the declines in maternity service usage have implications for women’s reproductive health and outcomes and infants’ safe delivery and survival.
This study makes the following recommendations based on the findings of this analysis, given that the COVID-19 outbreaks in Kenya and Ethiopia have potentially influenced localised interruptions of maternal health services, derailing progress towards SDG targets.
The countries’ governments must act in resolution to safeguard pregnant women, unborn babies, mothers and newborns and ensure they can get the prenatal and postnatal routine care they need as governments alter their healthcare systems to mitigate the adverse effects of COVID-19 as well as any future public health threats.
The government can also ensure that the continuity of maternal care services is adequate by appropriating budgeted funds equitably without diverting away from intended purposes, especially in the counties or states most affected by declines in maternal care services.
Potentially, reported declines infer increased non-facility deliveries during COVID-19; thus, requisite sensitisation (community health talks and advocacy activities, among others) should encourage women to have skilled birth deliveries. Additionally, incentivise women for skilled birth deliveries by creating an enabling environment at the health facilities (through adequate training of birth attendants and midwives and providing essential equipment).
We also recommend strengthening holistic reporting of health facility data in national data repositories, such as the HMIS, to capture public and private health facilities and ensure that the database is updated with new facilities offering healthcare. Additionally, governments, development partners and other stakeholders are encouraged to work together to improve HMIS data quality. This is a prerequisite to ensuring accuracy in data capture and inferences from any analysis employing such data sources to make sound policy recommendations to governments.
Strengths and limitations
This research possesses several notable strengths. First and foremost, it leverages routine health facility data, thereby offering the potential to supply real-time updates regarding the effects of COVID-19 on healthcare service usage. These datasets are generally characterised by increased frequency of data collection over an extended time frame, enhanced cost-effectiveness and expedited availability. Second, the study provides national and subnational estimates, facilitating decision-making for intervention planning at various administrative levels. Of particular significance is the capacity to unveil previously concealed changes in the data when analysed at the subnational level, which would otherwise remain obscured when examined solely at the national level. Furthermore, this investigation employs a comprehensive array of robust statistical methods for data analysis. These methods encompass geospatial techniques and counterfactual analyses, among others, enabling the presentation of a holistic view of the impact of COVID-19 on healthcare usage. Importantly, these analytical tools can be readily adapted for application in the context of other diseases and research domains. Lastly, the study conducts a comparative analysis of the COVID-19 impact in two distinct countries, offering valuable insights and lessons for other LMICs sharing similar demographic and healthcare profiles.
This study is not without limitations. The challenges in data consistent with routine health information systems could be expected to suffer lapses during external shocks to the healthcare system. Data accuracy is another challenge we encountered during analysis; HMIS databases are notorious for data quality issues, and using these data requires considerable cleaning and adjustment efforts. Additionally, the inherent nature and constraints of DHIS2 data did not allow the inclusion of confounding variables (such as urban and rural disaggregation) in the modelling. A critical potential limitation to our study is that it is predicated on the assumption that no external factors (beyond our control in measuring) would have caused interruptions to the healthcare system, such as inclement weather, power outages and individual and social factors. These could not be controlled for different ecological levels using aggregated health facility data. Therefore, our analysis should be interpreted within the context of health facility-based estimations of the disruption due to COVID-19.
