LESSONS LEARNED FROM COVID-19 MODELLING EFFORTS FOR POLICY DECISION-MAKING IN LOWER- AND MIDDLE-INCOME COUNTRIES (preprint)

Introduction: The COVID-19 pandemic had devastating health and socio-economic effects, partly due to mitigating policy choices. There is little evidence of approaches that guided policy decisions in settings that had limited modelling capacity pre-pandemic. We sought to identify knowledge translation mechanisms, enabling factors, and structures needed to translate modelled evidence to policy decisions effectively. Methods We utilised convergent mixed methods in a participatory action approach, with quantitative data from a survey and qualitative data from a scoping review, in-depth interviews, and workshop notes. Participants included researchers and policy actors involved in COVID-19 evidence generation and decision-making. They were mostly from lower- and middle-income countries (LMICs) in Africa, Southeast Asia, and Latin America. Quantitative and qualitative data integration occurred during data analysis through triangulation and during reporting in a narrative synthesis. Results We engaged 147 researchers and 57 policy actors from 28 countries. We found that the strategies required to use modelling evidence effectively include capacity building of modelling expertise and communication, improved data infrastructure, sustained funding, and dedicated knowledge translation platforms. The common knowledge translation mechanisms used during the pandemic included policy briefs, face-to-face debriefings, and dashboards. Some enabling factors for knowledge translation comprised solid relationships and open communication between researchers and policymakers, credibility of researchers, co-production of policy questions, and embedding researchers in policymaking spaces. Barriers included competition among modellers, negative attitude of policymakers towards research, political influences and demand for quick outputs. Conclusion Our findings led to the co-development of a knowledge translation framework useful in various settings to guide decision-making, especially for public health emergencies. Furthermore, we provide a contextualised understanding of knowledge translation for LMICs during the COVID-19 pandemic. Finally, we share key lessons on how knowledge translation from mathematical modelling complements the broader learning agenda related to pandemic preparedness and long-term investments in evidence-to-policy translation.

Essential Emergency and Critical Care as a health system response to critical illness and the COVID19 pandemic: What does it cost? (preprint)

Essential Emergency and Critical Care (EECC) is a novel approach to the care of critically ill patients, focusing on first-tier, low-cost care and designed to be feasible even in low-resourced and low-staffed settings. This is distinct from advanced critical care, usually conducted in ICUs with specialised staff, facilities and technologies. This paper estimates the incremental cost of EECC and advanced critical care for the planning of care for critically ill patients in low resource settings with Kenya and Tanzania as case studies.The incremental costing took a health systems perspective. A normative approach based on the ingredients defined through the recently published global consensus on EECC was used. The setting was a district hospital in which the patient is provided with the definitive care typically provided at that level for their condition. Quantification of resource use was based on COVID-19 as a tracer condition using clinical expertise. Local prices were used where available, and all costs were converted to USD2020.The costs per patient day of EECC is estimated to be 1.01 USD, 10.83 USD and 32.84 USD in Tanzania and 1.76 USD, 14.86 USD and 37.43 USD in Kenya, for moderate, severe and critical COVID-19 patients respectively. The cost per patient day of advanced critical care is estimated to be 13.11 USD and 17.33 USD for severe and 297.30 USD and 369.64 USD for critical COVID-19 patients in Tanzania and Kenya, respectively.EECC, an approach of providing the essential care to all critically ill patients, is low-cost. The components of EECC are basic and universal and, when assessed against the existing gaps in critical care coverage and costs of advanced critical care, suggest that it should be a priority area of investment for health systems around the globe.

Modelling the cost-effectiveness of essential and advanced critical care for COVID-19 patients in Kenya (preprint)

BackgroundCase management of symptomatic COVID-19 patients is a key health system intervention. The Kenyan government embarked to fill capacity gaps in essential and advanced critical care needed for the management of severe and critical COVID-19. However, given scarce resources, gaps in both essential and advanced critical care persist. This study assessed the cost-effectiveness of investments in essential and advanced critical care to inform the prioritization of investment decisions. MethodsWe employed a decision tree model to assess the incremental cost-effectiveness of investment in essential care (EC) and investment in both essential and advanced critical care (EC+ACC) compared to current health care provision capacity (status quo) for COVID-19 patients in Kenya. We used a health system perspective, and an inpatient care episode time horizon. Cost data was obtained from primary empirical analysis while outcomes data was obtained from epidemiological model estimates. We used univariate and probabilistic sensitivity analysis (PSA) to assess the robustness of the results. ResultsThe status quo option is more costly and less effective compared to investment in essential care and is thus dominated by the later. The incremental cost effectiveness ratio (ICER) of Investment in essential and advanced critical care (EC+ACC) was US $1,378.21 per DALY averted and hence not a cost-effective strategy when compared to Kenyas cost-effectiveness threshold (USD 908). ConclusionWhen the criterion of cost-effectiveness is considered, and within the context of resource scarcity, Kenya will achieve better value for money if it prioritizes investments in essential care before investments in advanced critical care. This information on cost-effectiveness will however need to be considered as part of a multi-criteria decision-making framework that uses a range of criteria that reflect societal values of the Kenyan society. Key questionsO_ST_ABSWhat is already known?C_ST_ABSO_LIThe COVID-19 pandemic is responsible for substantial health effects in low- and middle-income countries C_LIO_LIThe case management of COVID-19 is one of the key control interventions deployed by country health systems. C_LIO_LISimilar to other low- and middle-income countries, Kenya had substantial gaps in both essential and advanced critical care at the beginning of the pandemic. C_LI What are the new findings?O_LIProvision of essential care and advanced critical care for COVID-19 at the current health system capacity (status quo) was costly and the least effective strategy. C_LIO_LIInvestment in both essential care and advanced critical care for COVID-19 is not cost-effective in Kenya when compared to investment in essential care. C_LI What do the new findings imply?O_LIPrioritizing investments in filling capacity gaps in essential care before investing in filling capacity gaps in advanced critical care for COVID-19 is more cost-effective in Kenya C_LIO_LIThese findings are intended to inform the sequencing of investments in case management rather than the selection of either strategy, within a context of substantial resource constraint, and capacity gaps in both essential and advanced critical care or COVID-19 C_LIO_LIKenya will need to consider these findings on cost-effectiveness within a multi-criteria decision-making framework that use a range of criteria that reflect societal values. C_LI

COVID-19 Transmission Dynamics Underlying Epidemic Waves in Kenya (preprint)

Policy decisions on COVID-19 interventions should be informed by a local, regional and national understanding of SARS-CoV-2 transmission. Epidemic waves may result when restrictions are lifted or poorly adhered to, variants with new phenotypic properties successfully invade, or when infection spreads to susceptible sub-populations. Three COVID-19 epidemic waves have been observed in Kenya. Using a mechanistic mathematical model we explain the first two distinct waves by differences in contact rates in high and low social-economic groups, and the third wave by the introduction of a new higher-transmissibility variant. Reopening schools led to a minor increase in transmission between the second and third waves. Our predictions of current population exposure in Kenya (∼75% June 1st) have implications for a fourth wave and future control strategies. One Sentence Summary COVID-19 spread in Kenya is explained by mixing heterogeneity and a variant less constrained by high population exposure

Examining the Cost-effectiveness of Personal Protective Equipment for Formal Healthcare Workers in Kenya during the COVID-19 Pandemic (preprint)

Background: Healthcare workers are at a higher risk of COVID-19 infection during care encounters compared to the general population. Personal Protective Equipment (PPE) have been shown to protect COVID-19 among healthcare workers, however, Kenya has faced PPE shortages that can adequately protect all healthcare workers. We, therefore, examined the health and economic consequences of investing in PPE for healthcare workers in Kenya. Methods: We conducted a cost-effectiveness and return on investment (ROI) analysis using a decision-analytic model following the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) guidelines. We examined two outcomes: 1) the cost per healthcare worker death averted, and 2) the cost per healthcare worker COVID-19 case averted. We performed a multivariate sensitivity analysis using 10,000 Monte Carlo simulations. Results: Kenya would need to invest $3.12 million to adequately protect healthcare workers against COVID-19. This investment would avert 416 and 30,041 healthcare worker deaths and COVID-19 cases respectively. Additionally, such an investment would result in a societal ROI of $170.64 million – equivalent to an 11.04 times return. Conclusion: Despite other nationwide COVID-19 prevention measures such as social distancing, over 70% of healthcare workers will still be infected if the availability of PPE remains scarce. As part of the COVID-19 response strategy, the government should consider adequate investment in PPE for all healthcare workers in the country as it provides a large return on investment and it is value for money.

Examining Unit Costs for COVID-19 Case Management in Kenya (preprint)

IntroductionCase management for COVID-19 patients is one of key interventions in country responses to the pandemic. Countries need information on the costs of case management to inform resource mobilization, planning and budgeting, purchasing arrangements, and assessments of the cost-effectiveness of interventions. We estimated unit costs for COVID-19 case management for patients with asymptomatic, mild to moderate, severe, and critical COVID-19 disease in Kenya. MethodsWe estimated per patient per day unit costs of COVID-19 case management for patients that are asymptomatic and those that have mild to moderate, severe, and critical symptoms. For asymptomatic and mild to moderate patients, we estimated unit costs for home-based care and institutional (hospitals and isolation centers). We used an ingredients approach, adopted a health system perspective and patient episode of care as our time horizon. We obtained data on inputs and their quantities from COVID-19 case management guidelines, home based care guidelines, and human resource guidelines, and augmented this with data provided by three public covid-19 treatment hospitals in Kenya. We obtained input prices for services from a recent costing survey of 20 hospitals in Kenya and for pharmaceuticals, non-pharmaceuticals, devices and equipment from market price databases for Kenya. ResultsPer day per patient unit cost for asymptomatic patients and patients with mild to moderate COVID-19 disease under home based care are KES 1,993.01 (USD 18.89) and 1995.17 (USD 18.991) respectively. When these patients are managed in an isolation center of hospital, the same unit costs for asymptomatic patients and patients with mild to moderate disease are 7,415.28 (USD 70.29) and 7,417.44 (USD 70.31) respectively. Per day unit costs for patients with severe COVID-19 disease managed in general hospital wards and those with critical COVID-19 disease admitted in intensive care units are 12,570.75 (USD 119.16) and 59,369.42 (USD 562.79). ConclusionCOVID-19 case management costs are substantial. Unit costs for asymptomatic and mild to moderate COVID-19 patients in home-based care is 4-fold lower compared institutional care of the same patients. Kenya will not only need to mobilize substantial resources to finance COVID-19 case management but also explore additional service delivery adaptations that will reduce unit costs.

Revealing the extent of the COVID-19 pandemic in Kenya based on serological and PCR-test data (preprint)

Policy makers in Africa need robust estimates of the current and future spread of SARS-CoV-2. Data suitable for this purpose are scant. We used national surveillance PCR test, serological survey and mobility data to develop and fit a county-specific transmission model for Kenya. We estimate that the SARS-CoV-2 pandemic peaked before the end of July 2020 in the major urban counties, with 34 - 41% of residents infected, and will peak elsewhere in the country within 2-3 months. Despite this penetration, reported severe cases and deaths are low. Our analysis suggests the COVID-19 disease burden in Kenya may be far less than initially feared. A similar scenario across sub-Saharan Africa would have implications for balancing the consequences of restrictions with those of COVID-19.