Impact of COVID-19 on the neglected tropical diseases: a scoping review.

BACKGROUND: This study investigates the impact of the COVID-19 pandemic on the prevalence, management, and control of the neglected tropical diseases (NTDs) highlighting the current or prospective impact of COVID-19 on research and development funding for, and execution of, NTD programmes. This review was conducted to determine if, and how, NTDs were affected by COVID-19, and whether those effects will delay the elimination goals of the Sustainable Development goals. METHODS: Using open-source available data from policy and documentation from official websites of the relevant stakeholders including but not limited to World Health Organization (WHO) documents and policies, government foreign aid documents, and the Policy Cures G-Finder reports, this scoping review explored ongoing challenges to supporting research and development (R&D) for the NTDs and in maintaining NTD control programs; examined the constraints posed for NTD management by the pandemic from disruptions to healthcare services, reduction of finance and explored the potential long-term implications and consequences for those poorer, neglected populations in low and middle income-countries (LMICs). This was done by a scoping review literature search, publications were subject to an initial practical screening step to ensure the most relevant publications were selected for full screening, with the focus on scoping the designated topic of the impact of COVID-19 on NTDs. We further undertook an evaluation of the socio-economic factors exacerbating the impact of COVID-19 on NTD burden. RESULTS: Multiple disruptions and setbacks, likely to affect NTD programmes and progress towards their elimination targets were identified in this study. R&D funding for the NTDs and AIDs and TB has declined since the funding high point of 2019, and for malaria since the high point of 2018. Significant changes in allocation of R&D funding within the NTDs are observed post pandemic, likely because of prioritization among donors. Diseases for which the least R&D investment was reported in place, prior to the pandemic (mycetoma, taeniasis/cysticercosis, trachoma and Buruli ulcer) have been particularly impacted post pandemic. We identified specific NTDs including schistosomiasis, leprosy, and rabies that have been affected by the COVID-19 pandemic and disruptions caused to on ongoing NTD control and elimination programs. Pandemic restrictions disrupted essential medical supply manufacturing and distribution impacting immunization programs and hindered efforts to control the spread of infectious diseases. NTD programmes have experienced numerous setbacks including delays in mass drug administration programs (e.g. for schistosomiasis), cancelled or delayed vaccination programs (e.g. for rabies) and closure of testing facilities has resulted in reduced diagnosis, treatment, and disease elimination for all NTDs. Lockdowns and clinic closures causing disruption to essential healthcare services restricted NTD surveillance and treatment programs. Community fears around contracting COVID-19 exacerbated the constraints to service delivery. Disparities in global vaccine distribution have widened with LMICs facing limited access to vaccines and disruption to immunization programs. Finally, the pandemic has led to increased poverty with poor and marginalized communities, impacting nutrition, healthcare access and education all of which have long term implications for NTD management and control. CONCLUSIONS: The COVID-19 pandemic profoundly impacted global health research and global health equity. Attention and funding were diverted from all sectors, significantly affecting research and development efforts set out in the World Health Organization's NTD elimination Roadmaps. Ongoing changes to funding, economic crises, logistics and supply chain disruptions as well as deepening poverty has put a strain on already weak healthcare systems and exacerbated LMIC healthcare challenges. In particular, the delays and constraints to NTD management and elimination programs will have long-reaching consequences highlighting the need for global cooperation and renewed investment to put the NTD roadmap back on track. Targets and milestones are unlikely to be met without significant investment for recovery, in place.

Scottish Index of Multiple Deprivation (SIMD) indicators as predictors of mortality among patients hospitalised with COVID-19 disease in the Lothian Region, Scotland during the first wave: a cohort study.

BACKGROUND: Sars-CoV-2, the causative agent of COVID-19, has led to more than 226,000 deaths in the UK and multiple risk factors for mortality including age, sex and deprivation have been identified. This study aimed to identify which individual indicators of the Scottish Index of Multiple Deprivation (SIMD), an area-based deprivation index, were predictive of mortality. METHODS: This was a prospective cohort study of anonymised electronic health records of 710 consecutive patients hospitalised with Covid-19 disease between March and June 2020 in the Lothian Region of Southeast Scotland. Data sources included automatically extracted data from national electronic platforms and manually extracted data from individual admission records. Exposure variables of interest were SIMD quintiles and 12 indicators of deprivation deemed clinically relevant selected from the SIMD. Our primary outcome was mortality. Age and sex adjusted univariable and multivariable analyses were used to determine measures of association between exposures of interest and the primary outcome. RESULTS: After adjusting for age and sex, we found an increased risk of mortality in the more deprived SIMD quintiles 1 and 3 (OR 1.75, CI 0.99-3.08, p = 0.053 and OR 2.17, CI 1.22-3.86, p = 0.009, respectively), but this association was not upheld in our multivariable model containing age, sex, Performance Status and clinical parameters of severity at admission. Of the 12 pre-selected indicators of deprivation, two were associated with greater mortality in our multivariable analysis: income deprivation rate categorised by quartile (Q4 (most deprived): 2.11 (1.20-3.77) p = 0.011)) and greater than expected hospitalisations due to alcohol per SIMD data zone (1.96 (1.28-3.00) p = 0.002)). CONCLUSIONS: SIMD as an aggregate measure of deprivation was not predictive of mortality in our cohort when other exposure measures were accounted for. However, we identified a two-fold increased risk of mortality in patients residing in areas with greater income-deprivation and/or number of hospitalisations due to alcohol. In areas where aggregate measures fail to capture pockets of deprivation, exploring the impact of specific SIMD indicators may be helpful in targeting resources to residents at risk of poorer outcomes from Covid-19.

Segmentation and shielding of the most vulnerable members of the population as elements of an exit strategy from COVID-19 lockdown.

This study demonstrates that an adoption of a segmenting and shielding strategy could increase the scope to partially exit COVID-19 lockdown while limiting the risk of an overwhelming second wave of infection. We illustrate this using a mathematical model that segments the vulnerable population and their closest contacts, the 'shielders'. Effects of extending the duration of lockdown and faster or slower transition to post-lockdown conditions and, most importantly, the trade-off between increased protection of the vulnerable segment and fewer restrictions on the general population are explored. Our study shows that the most important determinants of outcome are: (i) post-lockdown transmission rates within the general and between the general and vulnerable segments; (ii) fractions of the population in the vulnerable and shielder segments; (iii) adherence to protective measures; and (iv) build-up of population immunity. Additionally, we found that effective measures in the shielder segment, e.g. intensive routine screening, allow further relaxations in the general population. We find that the outcome of any future policy is strongly influenced by the contact matrix between segments and the relationships between physical distancing measures and transmission rates. This strategy has potential applications for any infectious disease for which there are defined proportions of the population who cannot be treated or who are at risk of severe outcomes. This article is part of the theme issue 'Modelling that shaped the early COVID-19 pandemic response in the UK'.