Malawi’s maternal and neonatal COVID-19 surveillance platform was built for a strained system
The COVID-19 pandemic exposed a hard truth in maternal care: fragile health systems were asked to track a fast-moving infection while still protecting pregnancy, delivery, and newborn services. In Malawi, that challenge led to a national-level digital surveillance platform designed to capture maternal and neonatal COVID-19 data across the health system. The evaluation of that platform used a mixed-methods implementation science approach, a sensible choice for a tool that has to work not just on paper, but in clinics, wards, registries, and reporting chains under pressure.
The platform’s purpose was practical. Maternal age, high body mass index, chronic hypertension, and pre-existing diabetes all increase pregnancy risk, and SARS-CoV-2 added another layer of concern to already vulnerable pregnancies. A surveillance system in that setting has to do more than store numbers. It has to fit clinical routines, remain usable when staff are stretched, and produce data reliable enough to guide decisions about women and newborns who may be deteriorating quickly.
Implementation science, not software alone, determined the evaluation
The study did not treat the platform as a static digital product. Instead, it evaluated implementation process outcomes, the kind of evidence that asks whether a new system can actually be absorbed into routine care. Mixed-methods design is especially suited to that task because digital tools often fail for reasons that are invisible in simple usage metrics. A platform may be technically sound and still falter if staff find it cumbersome, if workflows do not align with clinical practice, or if the system adds burden without returning useful information.
Qualitative work was carried out in both high- and low-performing health facilities. That sampling strategy gives the evaluation a built-in contrast: sites with stronger performance can reveal what helps implementation, while low-performing sites can expose where adoption frays. Even so, the study’s own framing makes clear that this approach narrows interpretation to facilities with intermediate performance. In other words, the findings cannot be assumed to apply cleanly across the whole Malawian health system.
This matters because digital surveillance rarely behaves the same way in every setting. A platform used in a well-resourced maternity ward may look acceptable there and still break down where staffing is thinner, internet access is unstable, or data entry competes with urgent bedside care. Usability is not a generic property of software; it is a function of clinical environment, training, workload, and the degree to which the platform matches the way health workers actually document and escalate maternal and neonatal events.
The evaluation therefore sits at the intersection of informatics and obstetric care. Its real value lies in asking whether a national digital platform can support continuity of surveillance for pregnant women and newborns during a pandemic, when missed documentation can mean missed follow-up, delayed referral, or incomplete case identification.
A national digital system can only work if the front line can use it
A surveillance platform is only as strong as the last person entering data into it. If a nurse, midwife, or clinician has to slow down clinical care to complete a system that feels redundant or difficult to navigate, the platform may generate records but lose operational value. If the tool instead aligns with routine maternal and neonatal workflows, it can become part of care rather than an added administrative layer.
The evaluation’s focus on acceptability and usability is therefore clinically relevant. Acceptability speaks to whether health workers are willing to engage with the platform. Usability speaks to whether they can use it efficiently and correctly in the realities of care delivery. In maternal and neonatal COVID-19 surveillance, those two concepts are not abstract implementation terms. They affect whether infections, comorbidities, outcomes, and follow-up information are captured in time to inform care and public health response.
A digital platform also has to handle transitions in care. Maternal and neonatal cases often move between triage, labor ward, postnatal care, and newborn services. If surveillance data do not follow the patient across those points, the system becomes fragmented. During a pandemic, fragmentation is especially costly because infection status, obstetric complications, and newborn vulnerability may need to be tracked together rather than in isolated silos.
The study’s limitations define where its findings can and cannot travel
The most direct limitation is geographic and operational. Qualitative analysis in high- and low-performing facilities restricts interpretation to the middle ground of implementation performance, not the full continuum of care settings. Facilities with extreme constraints may face very different barriers, while top-performing sites may reveal use patterns that are not reproducible elsewhere. The evaluation also does not offer a picture of how the surveillance system would function at the primary healthcare level within Malawi’s health system.
That gap is substantial. Primary care is often where the earliest maternal and neonatal encounters occur, especially in health systems where community access and referral pathways shape who reaches higher-level facilities. If a national surveillance platform cannot be understood at that level, its system-wide usefulness remains partly untested. Data completeness, timeliness, and ease of entry are likely to differ when the platform moves away from higher-acuity facilities and into primary settings with fewer staff and less infrastructure.
One sentence carries the clinical weight of the paper: a national digital platform can look coherent in evaluation and still remain unproven where most patients first enter care.
The pandemic accelerated digital health experimentation across Africa, but implementation success depends on more than rollout. It depends on fit, durability, and whether frontline teams can sustain use without sacrificing clinical attention. For Malawi, this evaluation offers a structured look at a maternal and neonatal surveillance system created under emergency conditions, while also making clear that the primary healthcare tier remains an unanswered operational question.
The platform’s real-world value will hinge on whether it can move beyond intermediate performance settings and prove that it can work where maternal and neonatal care begins, not only where it is already better organized.