Search

BackgroundIncreasing the availability of antigen rapid diagnostic tests (Ag-RDTs) in low- and middle-income countries (LMICs) is key to alleviating global SARS-CoV-2 testing inequity (median testing rate in December 2021–March 2022 when the Omicron variant was spreading in multiple countries: high-income countries = 600 tests/100 000 people/day; LMICs = 14 tests/100 000 people/day). However, target testing levels and effectiveness of asymptomatic community screening to impact SARS-CoV-2 transmission in LMICs are unclear.MethodsWe used Propelling Action for Testing and Treating (PATAT), an LMIC-focused agent-based model to simulate coronavirus disease 2019 (COVID-19) epidemics, varying the amount of Ag-RDTs available for symptomatic testing at healthcare facilities and asymptomatic community testing in different social settings. We assumed that testing was a function of access to healthcare facilities and availability of Ag-RDTs. We explicitly modelled symptomatic testing demand from individuals without SARS-CoV-2 and measured impact based on the number of infections averted due to test-and-isolate.ResultsTesting symptomatic individuals yields greater benefits than any asymptomatic community testing strategy until most symptomatic individuals who sought testing have been tested. Meeting symptomatic testing demand likely requires at least 200–400 tests/100 000 people/day, on average, as symptomatic testing demand is highly influenced by individuals without SARS-CoV-2. After symptomatic testing demand is satisfied, excess tests to proactively screen for asymptomatic infections among household members yield the largest additional infections averted.ConclusionsTesting strategies aimed at reducing transmission should prioritize symptomatic testing and incentivizing test-positive individuals to adhere to isolation to maximize effectiveness.

Oral antivirals can potentially reduce the burden of COVID-19. However, low SARS-CoV-2 clinical testing rates in many low- and middle-income countries (LMICs) (mean Rt ≤ 1.2), increasing to 100 tests/100,000 people/day and allowing uncapped distribution of antivirals to LMICs (estimate = 26,000,000-90,000,000 courses/year for all LMICs), could avert up to 65% of severe cases, particularly in countries with older populations. For higher Rt, significant reductions in severe cases are only possible by substantially increasing testing rates or restricting clinical testing to those with higher risk of severe disease.

The first step in SARS-CoV-2 genomic surveillance is testing to identify people who are infected. However, global testing rates are falling as we emerge from the acute health emergency and remain low in many low- and middle-income countries (mean = 27 tests per 100,000 people per day). We simulated COVID-19 epidemics in a prototypical low- and middle-income country to investigate how testing rates, sampling strategies and sequencing proportions jointly impact surveillance outcomes, and showed that low testing rates and spatiotemporal biases delay time to detection of new variants by weeks to months and can lead to unreliable estimates of variant prevalence, even when the proportion of samples sequenced is increased. Accordingly, investments in wider access to diagnostics to support testing rates of approximately 100 tests per 100,000 people per day could enable more timely detection of new variants and reliable estimates of variant prevalence. The performance of global SARS-CoV-2 genomic surveillance programs is fundamentally limited by access to diagnostic testing.

Increasing the availability of antigen rapid diagnostic tests (Ag-RDTs) in low- and middle-income countries (LMICs) is key to alleviating global SARS-CoV-2 testing inequity (median testing rate in December 2021-March 2022 when the Omicron variant was spreading in multiple countries; high-income countries = 600 tests/100,000 people/day; LMICs = 14 tests/100,000 people/day). However, target testing levels and effectiveness of asymptomatic community screening to impact SARS-CoV-2 transmission in LMICs are unclear.We used PATAT, an LMIC-focused agent-based model to simulate COVID-19 epidemics, varying the amount of Ag-RDTs available for symptomatic testing at healthcare facilities and asymptomatic community testing in different social settings. We assumed that testing was a function of access to healthcare facilities and availability of Ag-RDTs. We explicitly modelled symptomatic testing demand from non-SARS-CoV-2 infected individuals and measured impact based on the number of infections averted due to test-and-isolate.Testing symptomatic individuals yields greater benefits than any asymptomatic community testing strategy until most symptomatic individuals who sought testing have been tested. Meeting symptomatic testing demand likely requires at least 200-400 tests/100,000 people/day on average as symptomatic testing demand is highly influenced by non-SARS-CoV-2 infected individuals. After symptomatic testing demand is satisfied, excess tests to proactively screen for asymptomatic infections among household members yields the largest additional infections averted.Testing strategies aimed at reducing transmission should prioritize symptomatic testing and incentivizing test-positive individuals to adhere to isolation to maximize effectiveness.

SummaryBackgroundIncreasing the availability of antigen rapid diagnostic tests (Ag-RDTs) in low- and middle-income countries (LMICs) is key to alleviating global SARS-CoV-2 testing inequity (median testing rate in December 2021-March 2022 when the Omicron variant was spreading in multiple countries; high-income countries=600 tests/100,000 people/day; LMICs=14 tests/ 100,000 people/day). However, target testing levels and effectiveness of asymptomatic community screening to impact SARS-CoV-2 transmission in LMICs are unclear.MethodsWe used PATAT, an LMIC-focused agent-based model to simulate COVID-19 epidemics, varying the amount of Ag-RDTs available for symptomatic testing at healthcare facilities and asymptomatic community testing in different social settings. We assumed that testing was a function of access to healthcare facilities and availability of Ag-RDTs. We explicitly modelled symptomatic testing demand from non-SARS-CoV-2 infected individuals and measured impact based on the number of infections averted due to test-and-isolate.ResultsTesting symptomatic individuals yields greater benefits than any asymptomatic community testing strategy until most symptomatic individuals who sought testing have been tested.Meeting symptomatic testing demand likely requires at least 200-400 tests/100,000 people/day on average as symptomatic testing demand is highly influenced by non-SARS-CoV-2 infected individuals. After symptomatic testing demand is satisfied, excess tests to proactively screen for asymptomatic infections among household members yields the largest additional infections averted.ConclusionsTesting strategies aimed at reducing transmission should prioritize symptomatic testing and incentivizing test-positive individuals to adhere to isolation to maximize effectiveness.

ispartof: ECLINICALMEDICINE vol:43 ispartof: location:England status: published

COVID-19 is the world’s first digital pandemic. Digital tools and technologies have been developed to track and trace the spread of the virus, screen for infection, and the pandemic has accelerated the use of digital technology in the delivery of healthcare. The continued development of these tools and technologies, the monitoring of the virus and the development of new tests, treatments and vaccines are dependent on the collection of and access to vast amounts of personal data. This includes clinical data, epidemiological data and public health data that may be collected from laboratories, medical records, wearables and smartphone apps. Previous public health emergencies (PHEs) have demonstrated the importance in making this data available, and early in the COVID-19 pandemic, there were calls for making all kinds of data, including clinical trial data, routine surveillance data, genetic sequencing, and data on the ongoing monitoring of disease control programmes, openly and rapidly available. As part of this, personal data on age, race, sex, health, ethnic group, and socioeconomic factors have been shared. This has helped led to the rapid development of COVID-19 interventions. It has also enabled the better understanding of factors contributing to difference in infection rates and effectiveness of tests, treatments, and vaccines. However, the use of this particularly sensitive data can infringe upon individual and group privacy, increase the risks of individual and group stigma and discrimination, and it may negatively impact already vulnerable, marginalised or minority populations. [...]

Countries around the world have implemented restrictions on mobility, especially cross-border travel to reduce or prevent SARS-CoV-2 community transmission. Rapid antigen testing (Ag-RDT), with on-site administration and rapid turnaround time may provide a valuable screening measure to ease cross-border travel while minimizing risk of local transmission. To maximize impact, we developed an optimal Ag-RDT screening algorithm for cross-border entry. Using a previously developed mathematical model, we determined the daily number of imported COVID-19 cases that would generate no more than a relative 1% increase in cases over one month for different effective reproductive numbers (Rt) and COVID-19 prevalence within the recipient country. We then developed an algorithm—for differing levels of Rt, arrivals per day, mode of travel, and SARS-CoV-2 prevalence amongst travelers—to determine the minimum proportion of people that would need Ag-RDT testing at border crossings to ensure no greater than the relative 1% community spread increase. When daily international arrivals and/or COVID-19 prevalence amongst arrivals increases, the proportion of arrivals required to test using Ag-RDT increases. At very high numbers of international arrivals/COVID-19 prevalence, Ag-RDT testing is not sufficient to prevent increased community spread, especially when recipient country prevalence and Rt are low. In these cases, Ag-RDT screening would need to be supplemented with other measures to prevent an increase in community transmission. An efficient Ag-RDT algorithm for SARS-CoV-2 testing depends strongly on the epidemic status within the recipient country, volume of travel, proportion of land and air arrivals, test sensitivity, and COVID-19 prevalence among travelers.

With the Covid-19 pandemic and the introduction of the WHO’s Essential Diagnostics List (EDL), increasing global attention is focused on the crucial role of diagnostics in achieving universal health coverage. To create national EDLs and to aid health system planning, it is vital to understand the most common conditions with which people present at primary care health facilities. We undertook a systematic review of the most common reasons for primary care visits in low- and middle-income countries. Six databases were searched for articles published between January 2009 and December 2019, with the search updated on MEDLINE to January 2021. Data on the most common patient reasons for encounter (RFEs) and provider diagnoses were collected. 17 of 22,279 screened articles were included. Most studies used unvalidated diagnostic classification systems or presented provider diagnosis data grouped by organ system, rather than presenting specific diagnoses. No studies included data from low-income countries. Only four studies (from Brazil, India, Nigeria and South Africa) using the ICPC-2 classification system contained RFE and provider diagnosis data and could be pooled. The top five RFEs from the four studies were headache, fever, back or low back symptom, cough and pain general/multiple sites. The top five diagnoses were uncomplicated hypertension, upper respiratory tract infection, type 2 diabetes, malaria and health maintenance/prevention. No psychological symptoms were among the top 10 pooled RFEs. There was more variation in top diagnoses between studies than top RFEs, showing the importance of creating location-specific lists of essential diagnostics for primary care. Future studies should aim to sample primary care facilities from across their country of study and use ICPC-3 to report both patient RFEs and provider diagnoses.

The COVID-19 pandemic has reasserted the central role of effective diagnostics in the response to outbreaks. But a lack of coordination still hampers widespread access to these critical tools. A diagnostics agenda for global health is urgently needed for the promotion of diagnostics as a global good and to ensure their delivery.

Increased awareness, interest and use of assistive technology (AT) presents substantial opportunities for many citizens to become, or continue being, meaningful participants in society. However, there is a significant shortfall between the need for and provision of AT, and this is patterned by a range of social, demographic and structural factors. To seize the opportunity that assistive technology offers, regional, national and sub-national assistive technology policies are urgently required. This paper was developed for and through discussion at the Global Research, Innovation and Education on Assistive Technology (GREAT) Summit; organized under the auspices of the World Health Organization's Global Collaboration on Assistive Technology (GATE) program. It outlines some of the key principles that AT polices should address and recognizes that AT policy should be tailored to the realities of the contexts and resources available. AT policy should be developed as a part of the evolution of related policy across a number of different sectors and should have clear and direct links to AT as mediators and moderators for achieving the Sustainable Development Goals. The consultation process, development and implementation of policy should be fully inclusive of AT users, and their representative organizations, be across the lifespan, and imbued with a strong systems-thinking ethos. Six barriers are identified which funnel and diminish access to AT and are addressed systematically within this paper. We illustrate an example of good practice through a case study of AT services in Norway, and we note the challenges experienced in less well-resourced settings. A number of economic factors relating to AT and economic arguments for promoting AT use are also discussed. To address policy-development the importance of active citizenship and advocacy, the need to find mechanisms to scale up good community practices to a higher level, and the importance of political engagement for the policy process, are highlighted. Policy should be evidence-informed and allowed for evidence-making; however, it is important to account for other factors within the given context in order for policy to be practical, authentic and actionable. Implications for Rehabilitation The development of policy in the area of asssitive technology is important to provide an overarching vision and outline resourcing priorities. This paper identifies some of the key themes that should be addressed when developing or revising assistive technology policy. Each country should establish a National Assistive Technology policy and develop a theory of change for its implementation.