Understanding the Potential Impact of Different Drug Properties On SARS-CoV-2 Transmission and Disease Burden: A Modelling Analysis

Background The public health impact of the COVID-19 pandemic has motivated a rapid search for potential therapeutics, with some key successes. However, the potential impact of different treatments, and consequently research and procurement priorities, have not been clear. Methods Using a mathematical model of SARS-CoV-2 transmission, COVID-19 disease and clinical care, we explore the public-health impact of different potential therapeutics, under a range of scenarios varying healthcare capacity, epidemic trajectories; and drug efficacy in the absence of supportive care. Results The impact of drugs like dexamethasone (delivered to the most critically-ill in hospital and whose therapeutic benefit is expected to depend on the availability of supportive care such as oxygen and mechanical ventilation) is likely to be limited in settings where healthcare capacity is lowest or where uncontrolled epidemics result in hospitals being overwhelmed. As such, it may avert 22% of deaths in high-income countries but only 8% in low-income countries (assuming R=1.35). Therapeutics for different patient populations (those not in hospital, early in the course of infection) and types of benefit (reducing disease severity or infectiousness, preventing hospitalisation) could have much greater benefits, particularly in resource-poor settings facing large epidemics. Conclusions Advances in the treatment of COVID-19 to date have been focussed on hospitalised-patients and predicated on an assumption of adequate access to supportive care. Therapeutics delivered earlier in the course of infection that reduce the need for healthcare or reduce infectiousness could have significant impact, and research into their efficacy and means of delivery should be a priority

Dietary diversity, socioeconomic status and maternal body mass index (BMI): quantile regression analysis of nationally representative data from Ghana, Namibia and Sao Tome and Principe

OBJECTIVES: To (a) assess the association between dietary diversity (DD) score, socioeconomic status (SES) and maternal body mass index (BMI), and (b) the variation of the effects of DD and SES at different points of the conditional distribution of the BMI. METHODS: The study used Demographic and Health Surveys round 5 data sets from Ghana, Namibia and Sao Tome and Principe. The outcome variable for the analysis was maternal BMI. The DD score was computed using 24-hour dietary recall data. Quantile regression (QR) was used to examine the relationship between DD and SES, and maternal BMI, adjusting for other covariates. The QR allows the covariate effects to vary across the entire distribution of maternal BMI. RESULTS: Women who consumed an additional unit of DD achieved an increase of 0.245 in BMI for those in the 90th quantile in Ghana. The effect of household wealth increases for individuals across all quantiles of the BMI distribution and in all the 3 countries. A unit change in the household wealth score was associated with an increase of 0.038, 0.052 and 0.065 units increase in BMI for individuals in the 5th quantile in Ghana, Namibia and Sao Tome and Principe, respectively. Also, 0.237, 0.301 and 0.174 units increased for those in the 90th quantile in Ghana, Namibia and Sao Tome and Principe, respectively. Education had a significant positive effect on maternal BMI across all quantiles in Namibia and negative effect at the 5th, 10th and 90th quantiles in Sao Tome and Principe. CONCLUSIONS: There is heterogeneity in the effects of DD and SES on maternal BMI. Studies focusing on the effects of diet and socioeconomic determinants on maternal BMI should examine patterns of effects at different points of the conditional distribution of the BMI and not just the average effect

Evaluating controlled human malaria infection in Kenyan adults with varying degrees of prior exposure to Plasmodium falciparum using sporozoites administered by intramuscular injection.

BACKGROUND: Controlled human malaria infection (CHMI) studies are a vital tool to accelerate vaccine and drug development. As CHMI trials are performed in a controlled environment, they allow unprecedented, detailed evaluation of parasite growth dynamics (PGD) and immunological responses. However, CHMI studies have not been routinely performed in malaria-endemic countries or used to investigate mechanisms of naturally-acquired immunity (NAI) to Plasmodium falciparum. METHODS: We conducted an open-label, randomized CHMI pilot-study using aseptic, cryopreserved P. falciparum sporozoites (PfSPZ Challenge) to evaluate safety, infectivity and PGD in Kenyan adults with low to moderate prior exposure to P. falciparum (Pan African Clinical Trial Registry: PACTR20121100033272). RESULTS: All participants developed blood-stage infection confirmed by quantitative polymerase chain reaction (qPCR). However one volunteer (110) remained asymptomatic and blood-film negative until day 21 post-injection of PfSPZ Challenge. This volunteer had a reduced parasite multiplication rate (PMR) (1.3) in comparison to the other 27 volunteers (median 11.1). A significant correlation was seen between PMR and screening anti-schizont Enzyme Linked Immunosorbent Assays (ELISA) OD (p = 0.044, R = -0.384) but not when volunteer 110 was excluded from the analysis (p = 0.112, R = -0.313). CONCLUSIONS: PfSPZ Challenge is safe and infectious in malaria-endemic populations and could be used to assess the efficacy of malaria vaccines and drugs in African populations. Whilst our findings are limited by sample size, our pilot study has demonstrated for the first time that NAI may impact on PMR post-CHMI in a detectable fashion, an important finding that should be evaluated in further CHMI studies

Understanding the potential impact of different drug properties on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission and disease burden: a modelling analysis

Background The public health impact of the coronavirus disease 2019 (COVID-19) pandemic has motivated a rapid search for potential therapeutics, with some key successes. However, the potential impact of different treatments, and consequently research and procurement priorities, have not been clear. Methods Using a mathematical model of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission, COVID-19 disease and clinical care, we explore the public-health impact of different potential therapeutics, under a range of scenarios varying healthcare capacity, epidemic trajectories; and drug efficacy in the absence of supportive care. Results The impact of drugs like dexamethasone (delivered to the most critically-ill in hospital and whose therapeutic benefit is expected to depend on the availability of supportive care such as oxygen and mechanical ventilation) is likely to be limited in settings where healthcare capacity is lowest or where uncontrolled epidemics result in hospitals being overwhelmed. As such, it may avert 22% of deaths in high-income countries but only 8% in low-income countries (assuming R = 1.35). Therapeutics for different patient populations (those not in hospital, early in the course of infection) and types of benefit (reducing disease severity or infectiousness, preventing hospitalization) could have much greater benefits, particularly in resource-poor settings facing large epidemics. Conclusions Advances in the treatment of COVID-19 to date have been focused on hospitalized-patients and predicated on an assumption of adequate access to supportive care. Therapeutics delivered earlier in the course of infection that reduce the need for healthcare or reduce infectiousness could have significant impact, and research into their efficacy and means of delivery should be a priority

Understanding the Potential Impact of Different Drug Properties On SARS-CoV-2 Transmission and Disease Burden: A Modelling Analysis

Background The public health impact of the COVID-19 pandemic has motivated a rapid search for potential therapeutics, with some key successes. However, the potential impact of different treatments, and consequently research and procurement priorities, have not been clear. Methods Using a mathematical model of SARS-CoV-2 transmission, COVID-19 disease and clinical care, we explore the public-health impact of different potential therapeutics, under a range of scenarios varying healthcare capacity, epidemic trajectories; and drug efficacy in the absence of supportive care. Results The impact of drugs like dexamethasone (delivered to the most critically-ill in hospital and whose therapeutic benefit is expected to depend on the availability of supportive care such as oxygen and mechanical ventilation) is likely to be limited in settings where healthcare capacity is lowest or where uncontrolled epidemics result in hospitals being overwhelmed. As such, it may avert 22% of deaths in high-income countries but only 8% in low-income countries (assuming R=1.35). Therapeutics for different patient populations (those not in hospital, early in the course of infection) and types of benefit (reducing disease severity or infectiousness, preventing hospitalisation) could have much greater benefits, particularly in resource-poor settings facing large epidemics. Conclusions Advances in the treatment of COVID-19 to date have been focussed on hospitalised-patients and predicated on an assumption of adequate access to supportive care. Therapeutics delivered earlier in the course of infection that reduce the need for healthcare or reduce infectiousness could have significant impact, and research into their efficacy and means of delivery should be a priority