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Essential Emergency and Critical Care (EECC) is a novel approach to the care of critically ill patients, focusing on first-tier, effective, low-cost, life-saving 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 Tanzania and Kenya. 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 USD, 11 USD and 33 USD in Tanzania and 2 USD, 14 USD and 37 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 USD and 294 USD in Tanzania and USD 17 USD and 345 USD in Kenya for severe and critical COVID-19 patients, respectively. EECC is a novel approach for providing the essential care to all critically ill patients. The low costs and lower tech approach inherent in delivering EECC mean that EECC could be provided to many and suggests that prioritizing EECC over ACC may be a rational approach when resources are limited. [ABSTRACT FROM AUTHOR]

Objectives This paper presents a simulation model for evaluating the possible effects of a screening and vaccination campaign against Human Papillomavirus [HPV] in Kenya. Method A System Dynamics model was developed using the iThink™ computer simulation package. The model was based on data extracted from epidemiological, demographic and published research and where data was not available, expert opinion was sought. The deterministic model stratified the population by vaccination status, screening status and HPV infection status. The model was simulated to estimate outputs for the next 50 years from 2011. Cost Utility indicators of Disability Adjusted Life Years (DALYs) and cost per averted DALY were used for economic evaluation. Results The model predicted that catch up vaccination had the greatest impact in reducing the prevalence of cervical cancer. This was followed by Primary vaccination, with early detection through Screening having the lowest impact of the three choices of interventions in respect of averted cases of cervical cancer and DALY estimates. Conclusion Kenya as a country should consider adoption of secondary /catch up vaccination as an immediate measure to curb cervical cancer followed by primary vaccination of pre- adolescent girls. Screening should be a complementary measure(s). This model provides a policy decision support vehicle that can allow for choice between different interventions based on their expected outcomes. It also allows modification to accommodate new research results and information to assess the clinical impact of different policies and interventions in cervical cancer management in Kenya. [ABSTRACT FROM AUTHOR]