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Covid-19 decision support tool for low and middle income countries

This simple framework can be used by policymakers of low and middle income countries (LMICs) to assess whether the country should impose tougher stringent measures to reduce the spread of covid-19 or may consider relaxing them

Scroll down for the interactive tool

November 2020

Authors: Rashid Zaman1 and Lisa White2      

1 Health and Nutrition Portfolio, Oxford Policy Management, Oxford, United Kingdom.
2 Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom.

Policymakers in low- and middle-income countries (LMICs) are grappling with the dilemma of whether to impose or release stringent measures to control the spread of covid-19. In high income countries, the reproductive number (R0) of the virus is used to guide these decisions. However, most LMICs do not have the robust healthcare systems and widespread testing capacity necessary to generate the reliable, representative data required to accurately determine R0. Many LMICs also have other complex factors that are often unique to each country, which may have important implications for these decisions. Here, we summarise ten key factors that could play an important role in these decisions, with the first five in support of restrictions and the remaining five opposing them.

Factors affecting decisions on covid-19 stringent measures

Health system capacity: In LMICs that have a limited health system capacity, an unmitigated covid-19 epidemic could overwhelm the system. In such a scenario, tougher measures aimed at ‘flattening the epidemic curve’ and delaying the epidemic peak to ensure that healthcare worers have adequate personal protective equipment (PPE) and training are a fundamental strategy for saving lives.

Vaccination: There are more than 200 vaccine candidates under development, as an effective and safe vaccine against SARS-CoV-2 is currently the most desirable solution to control the pandemic. Imposing restrictions could save lives by reducing the number of people who become infected prior to a vaccine becoming available.

New and existing drugs: Numerous clinical trials are ongoing to identify lifesaving treatments for covid-19. Some treatments have already proven to be effective in reducing the severity and/or duration of covid-19 (e.g. dexamethasone).

New knowledge: Scientists and clinicians are continuously gaining new insights into the risk factors, clinical manifestations and potential treatments for some of the complications associated with covid-19.

Virulence: A common property of zoonotic diseases, such as covid-19, is that the virulence of the pathogen gradually decreases as it is transmitted among humans. This has yet to be proved to be the case for SARS-CoV-2, but there is possibility that SARS-CoV-2 will also mutate into a milder form globally and stricter measure may buy some time for that to happen.

Socioeconomic disruption: The restrictive measures imposed to control the spread of covid-19 have serious negative impacts on every aspect of people’s lives and livelihoods, including the economy, food security, social care, education, law and order and more. These impacts can be even more pronounced in LMICs, and this is probably the strongest argument in favour of releasing stringent measures.

Impact on other illnesses: Stringent measures to contain covid-19 are also having direct negative impacts on other diseases; again, LMICs are especially hard hit. There have been reports of people not receiving either routine or emergency healthcare, children not being vaccinated and family planning services not being offered, all of which make it harder for LMICs to continue imposing strict measures to limit transmission of the virus.

Age structure: The morbidity and mortality of covid-19 is highly correlated with age, with elderly people disproportionality affected by the disease. Since the proportion of elderly people is lower in LMICs than in HICs, it may be easier to shield those that are most vulnerable and open the economy.

Compliance: Unlike some of the worst affected Western countries, most LMICs introduced strict control measures before widespread community transmission of covid-19 had begun, making it even more difficult to continue restrictions for an indefinite period.

Sero-prevalence: SARS-CoV-2 exhibits highly efficient human to human transmission; therefore, some have assumed that a large proportion of the population has already been or soon will be infected and subsequently become immune, for at least some time.
 

The decision support tool

Together, these factors make it extremely difficult for policymakers in LMICs to undertake objective evaluations and then make informed decisions whether to impose or release stringent control measures. Therefore, we have designed a decision support tool that can provide a framework for supporting evidence-based, context-specific decision-making on this matter.

Here we have included an interactive version of the tool that generates score and indicating the suggested measures. With this tool scores can be generated from 0 to 20. Lower score suggests tougher measures and higher score indicate that the restrictions could be lifted.

The tool can be further customised and contextualised by adding additional factors and using different weightings. We understand that the decisions we have alluded to are a function of a complex set of issues, and it is not possible to explore the full complexity of this topic in this brief overview. However, we hope that this simple tool could at least help policymakers to consider all factors relevant to their specific context and then make an informed decision, particularly during a possible second wave of the pandemic.

Acknowledgement

Authors are grateful to Olivier Celhay for developing the interactive decision making web-tool and to Adam Bodley for peer reviewing and copyediting this article.