Summary box
Globally, forecasting is rapidly gaining acceptance in healthcare and its use in public
health emergencies like the COVID-19 pandemic has been beneficial to improve emergency
preparedness and response towards the pandemic, particularly during the early and
peak phases.
Despite these benefits, forecasting capacity, largely in terms of expertise and support
systems, remains significantly limited in Africa, where the burden of public health
emergencies is highest.
Given the syndemics understanding of public health emergencies as extended by the
COVID-19 pandemic, we shared our viewpoint on the need to develop a sustainable forecasting
capacity in the African region for better health and social outcomes during and after
public health emergencies in the region, and globally.
Forecasting is an important aspect of decision-making in health and other social aspects
of human life. Forecasting can simply be defined as the process of making probabilities
about a real-world event using existing data built in a mathematical model.1 This
understanding underpins why forecasting is sometimes used interchangeably with the
word ‘modelling’. Forecasting capacity describes a system that comprises of surveillance
database, experts and relevant technologies, and it remains an indispensable workforce
development need for promoting data-driven decision-making in health, as frequently
advocated by the WHO.2 Generally, the usefulness and usability of forecasting is one
that is not unknown or unbeneficial to most people across the world, particularly
in non-emergency situations, from its use in daily weather reporting through global
projections on economy, and diseases burden. Similarly, from epidemiological perspective,
evidence from various forecasting models was observed to have played a major role
to improve emergency response in past disease outbreaks (eg, Ebola) and towards the
COVID-19 pandemic in the areas not limited to SARS-CoV2 patterns determination, containment
and mitigation measures implementation, risk communication, resource management and
vaccine development.3–8
Despite the demonstrated availability of forecasting capacity and its associated benefits
on health protection at the global level, unfortunately, the ownership and usage of
forecasting knowledge capita in public health emergency management remain significantly
limited at the regional level as laid bare by the COVID-19 pandemic, with Africa being
the most disproportionately impacted region, despite having a record high figure of
over 100 public health emergencies annually compared with other regions of the world.9
This disparity in forecasting capacity is reflected in current forecasting evidence
on COVID-19 pandemic, where most of the studies were either conducted in the developed
regions or for Africa by foreign experts such as in a study by Frost and colleagues.8
In addition, while anecdotal evidence shows that forecasting capacity exists in some
settings in Africa such as academia, governments, non-governmental organisations (NGOs),
this capacity is largely under-resourced, uncoordinated and short-term probably due
to weak surveillance systems and lack of national emergency forecasting centres or
forecasting units within the existing national public health institutes. Other reasons
for the ill-developed forecasting capacity in Africa could as well be attributed to
the lack of political will and weak partnerships between the government and the academia,
where most of the forecasting experts are housed. Notwithstanding, it is desirable
for the African region to increase training, research and funding investments in forecasting
capacity development of its workforce for efficient management of public health emergencies
including natural disasters and humanitarian crises.
However, given the forecasting capacity gaps in most health systems in Africa, one
can only wonder what would have informed public health decisions specific to containment
and mitigation, supplies procurement and risk communication in Africa during the COVID-19
pandemic. It is on this premise that the following essential questions need to be
asked: were the public health decisions made in the African region during the COVID-19
pandemic informed by local forecasting evidence or colloquial evidence or both? Were
the decisions a carbon-copy of global forecasting evidence or were the global forecasting
evidence further contextualised with local forecasting or other scientific evidence?
How would any of this forecasting evidence have influenced the level of community
trust of and adherence to public health measures such as lockdown and vaccine administration?
Have the decision-making processes between the public health professionals and policy
makers, including methodologies, strategies, challenges, and emerging issues, been
documented for future reference?
Certainly, these questions need to be systematically addressed for better decision-making
in future pandemics. More so, these questions align with the call for reflective thinking
and bold changes in the COVID-19 pandemic era as encouraged by Morgan and colleagues.10
In the same vein, it was the authors’ expectation that national public health institutes
should be responsible for conducting or coordinating forecasting analysis of surveillance
data to guide local public health actions; however, reported experiences from the
field suggest the contrary. For example, in Nigeria, most of the public health actions
implemented during the COVID-19 pandemic appear to have been largely guided by foreign
evidence and strategies. During the peak of the COVID-19 pandemic, we witnessed the
political leaders taking a centre stage in COVID-19 risk communication to the Nigerian
public through televised presidential task force meetings like in the USA, even when
realities suggest that there is lack of community trust in the politicians in the
country. Perhaps the role of this strategy on adherence to public health measures
during COVID-19 pandemic needs to be investigated and addressed carefully for best
practices.
Furthermore, while a case was made by Morgan and colleagues on the relevance of national
forecasting capacities, a strategic action plan for achieving this mandate was not
specified. Likewise, our call for forecasting capacity development in Africa is consistent
with the submission of Diouf and colleagues, who reported the need to contextualise
forecasting models in Africa.11 A vision we believe would be best achieved with local
expertise given context effects on results interpretation and decision-making. Equally,
the WHO Regional Office for Africa (WHO AFRO)’s commitment to guarantee health security
in Africa through its emergency response flagship programmes that were launched in
early 2022 further supports our opinion as well.9 Even though the WHO AFRO demonstrated
forecasting competency during the early stage of the COVID-19 pandemic to understand
the trajectory of SARS-CoV2 in the African region and also identified workforce development
as one of the core pillars of its emergency response flagship programmes for safeguarding
health in the region,5 9 it did not mention forecasting or modelling as part of the
required training competencies.
Nevertheless, we anticipate that the WHO AFRO’s emergency response flagship programmes
will leverage on some local capacity-promoting emergency management initiatives, in
which the WHO AFRO is inextricably part of, such as the Global Research and Analyses
for Public Health (GRAPH) network and the WHO Hub for Pandemic and Epidemic Intelligence
among others. This is because, for example, the GRAPH network and WHO Hub for Pandemic
and Epidemic Intelligence, which seek to strengthen surveillance systems and data
analytics for improved decision-making during public health emergencies in the African
region and globally, respectively, have recognised modelling as an essential component
of their activities.12 13 Notably, the establishment of the GRAPH network—a group
of African multidisciplinary scientists and international collaborators—during the
early phase of the COVID-19 pandemic has remained very instrumental to the continued
understanding of the COVID-19 pandemic dynamics in the African region.14–17 Certainly,
with these developments, we believe that the WHO AFRO and other African health partners
are already well positioned to support the development of a sustainable forecasting
capacity in Africa for future pandemics as well as other emergencies.
Central to this course is the adaptation of existing national public health emergency
systems to meet the syndemics realities of emergencies as explicitly demonstrated
by the COVID-19 pandemic. The COVID-19 pandemic and existing inequity has broadened
our understanding of syndemics in public health emergencies through its concurrent
complex interactions with comorbidities (eg, hypertension, diabetes) at the biological
level and social issues (eg, economic contraction, food scarcity) at the societal
level, which worsens public health outcomes and eventually delay emergency recovery.18–20
In practice, since the response to the COVID-19 pandemic has been multisectoral involving
sectors not limited to health, social and economic, a multisectoral approach is also
logically warranted to collect accurate, quality and real-time data in an integrated
format that truly reflect a real-world scenario for forecasting and its applicability
in the field. In fact, with the well-known realities in the African region such as
weak health systems and scarce resources, we argue that over-reliance on foreign forecasting
evidence, expertise and technologies in Africa not only risks poor public health outcomes
in the region given contextual differences, but also globally due to spill-over effects,
as currently being observed with emerging SARS-CoV2 variants in regions of the world,
particularly Africa, with low vaccine coverage rates due to lack of local vaccine
manufacturing capacity.
Therefore, there is an unmet need to urgently develop a sustainable forecasting capacity
that is rooted on syndemics approach in Africa to improve innovations, knowledge sharing
and coordination for context-specific, holistic and efficient public health emergency
management in the region. We recommend that the strategy for developing a public health
emergency forecasting capacity should be one that reinforces multisectoral and multilevel
collaboration, coordination and commitment among relevant stakeholders. The stakeholders
should include but not limited to the community, centres for disease control (CDC),
academia, national emergency management agencies, food sectors, finance departments,
national statistics agencies, faith-based organisations, NGOs, communication agencies,
political forums and international partners. Also, the capacity should be built such
that it ensures data capture, data integration and data dissemination from the community
level through the regional to the global level using a syndemics-oriented real-time
tool developed based on the ‘FAIR guiding principles of data management’, namely,
findability, accessibility, interoperability and reusability.21 And, to ensure sustainability
of this initiative, stakeholders should consider the establishment of forecasting
association, conference, training fellowship and research grant at the regional level
with representation nationally as well.
More importantly, we think that the real question that should be asked is, how do
we proceed from here? As answer to this question is context-specific, any suggested
solution would, however, not always be a one-size-fits-all solution, and its applicability
would need to be carefully reviewed, putting into consideration the realities of existing
resources and the political landscape of the study setting. Nonetheless, we believe
that our viewpoint is a step in the right direction to stimulate timely discussion
among the WHO Hub for Pandemic and Epidemic Intelligence, WHO AFRO, Africa CDC, national
public health institutes, national governments, academia, funders and other stakeholders
on development of sustainable forecasting capacity in Africa in addition to ongoing
discussions towards strengthening public health emergency management in the region
and ensuring global health security.