The 10-year health impact, economic impact, and return on investment of the South African molecular diagnostics programme for HIV, Tuberculosis and SARS-CoV-2 (preprint)

To ensure there is adequate investment into diagnostics, an understanding of the magnitude of impact and return on investment is necessary. We therefore sought to understand the health and economic impacts of the molecular diagnostic programme in South Africa, to deepen the under-standing on the broad value of diagnostics and guide future healthcare investments. We calcu-lated the 10-year (where data were available) total cost and DALYs averted associated with molecular diagnosis of molecular TB testing (2013-2022), HIV viral load monitoring (2013-2022), early infant diagnosis of HIV infection (2013-2022), and SARS-CoV-2 testing (2020-2022). We then calculated the economic value associated with those health gains and subsequent return on investment. Since the inception of the molecular diagnostics programme in South Africa, 3,035,782 DALYs have been averted as a direct consequence of this pro-gramme. This has generated an estimated $20.5 billion in economic value due to these health gains. The return on investment varied by specific diagnostic test (19.0 for tuberculosis, 1.4 for HIV viral load testing, 64.8 for early infant diagnosis of HIV, and 2.5 for SARS-CoV-2), for an average of 9.9 for the entire molecular diagnostics programme between 2013 and 2022- or $9.9 of value for each $1 invested. The molecular diagnostics programme in South Africa gen-erated a significant amount of health gains and economic value associated with these health gains, and the return-on-investment rivals other high-impact public health interventions such as childhood vaccination. Consequently, the molecular diagnostics programme in South Africa is highly impactful, and will continue to be an excellent investment of South African public health expenditure.

Strategies for using antigen rapid diagnostic tests to reduce transmission of SARS-CoV-2 in low- and middle-income countries: a mathematical modelling study (preprint)

Background 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. Methods 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. Findings 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 ~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. Interpretation Testing strategies aimed at reducing transmission should prioritize symptomatic testing and incentivizing test-positive individuals to adhere to isolation to maximize effectiveness.

Low testing rates limit the ability of genomic surveillance programs to monitor SARS-CoV-2 variants: a mathematical modelling study (preprint)

Background Genomic surveillance is essential for monitoring the emergence and spread of SARS-CoV-2 variants. SARS-CoV-2 diagnostic testing is the starting point for SARS-CoV-2 genomic sequencing. However, testing rates in many low- and middle-income countries (LMICs) are low (mean = 27 tests/100,000 people/day) and global testing rates are falling in the post-crisis phase of the pandemic, leading to spatiotemporal biases in sample collection. Various public health agencies and academic groups have produced recommendations on sample sizes and sequencing strategies for effective genomic surveillance. However, these recommendations assume very high volumes of diagnostic testing that are currently well beyond reach in most LMICs. Methods To investigate how testing rates, sequencing strategies and the degree of spatiotemporal bias in sample collection impact variant detection and monitoring outcomes, we used an individual-based model to simulate COVID-19 epidemics in a prototypical LMIC. Within the model, we simulated a range of testing rates, accounted for likely testing demand and applied various genomic surveillance strategies, including sentinel surveillance. Findings Diagnostic testing rates play a substantially larger role in monitoring the prevalence and emergence of new variants than the proportion of samples sequenced. To enable timely detection and monitoring of emerging variants, programs should achieve average testing rates of at least 100 tests/100,000 people/day and sequence 5-10% of test-positive specimens, which may be accomplished through sentinel or other routine surveillance systems. Under realistic assumptions, this averages to ~10 samples for sequencing/1,000,000 people/week. Interpretation For countries where testing capacities are low and sample collection is spatiotemporally biased, surveillance programs should prioritize investments in wider access to diagnostic testing to enable more representative sampling, ahead of simply increasing quantities of sequenced samples. Funding European Research Council, the Rockefeller Foundation, and the Governments of Germany, Canada, UK, Australia, Norway, Saudi Arabia, Kuwait, Netherlands and Portugal.

Mapping the antigenic diversification of SARS-CoV-2 (preprint)

Large-scale vaccination campaigns have prevented countless SARS-CoV-2 infections, hospitalizations and deaths. However, the emergence of variants that escape from immunity challenges the effectiveness of current vaccines. Given this continuing evolution, an important question is when and how to update SARS-CoV-2 vaccines to antigenically match circulating variants, similar to seasonal influenza viruses where antigenic drift necessitates periodic vaccine updates. Here, we studied SARS-CoV-2 antigenic drift by assessing neutralizing activity against variants-of-concern (VOCs) of a unique set of sera from patients infected with a range of VOCs. Infections with ancestral or Alpha strains induced the broadest immunity, while individuals infected with other VOCs had more strain-specific responses. Omicron was substantially resistant to neutralization by sera elicited by all other variants. Antigenic cartography revealed that all VOCs preceding Omicron belong to one antigenic cluster, while Omicron forms a new antigenic cluster associated with immune escape and likely requiring vaccine updates to ensure vaccine effectiveness.

Optimal use of COVID19 Ag-RDT screening at border crossings to prevent community transmission: a modeling analysis (preprint)

Background 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. Methods 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) of 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. Findings 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 for lower levels of Rt. In these cases, Ag-RDT screening would need to be supplemented with other measures to prevent an increase in community transmission. Interpretation An efficient Ag-RDT algorithm for SARS-CoV-2 testing depends strongly on Rt, volume of travel, proportion of land and air arrivals, test sensitivity, and COVID-19 prevalence among travelers. Funding USAID, Government of the Netherlands

Changes in HIV Treatment Differentiated Care Utilization During the COVID-19 Pandemic in Zambia (preprint)

BackgroundDifferentiated service delivery (DSD) models aim to lessen the burden of HIV treatment on patients and providers in part by reducing requirements for facility visits and extending dispensing intervals. With the advent of the COVID-19 pandemic, minimizing patient contact with healthcare facilities and other patients, while maintaining treatment continuity and avoiding loss to care, has become more urgent, resulting in efforts to increase DSD uptake. We assessed the extent to which DSD coverage and antiretroviral treatment (ART) dispensing intervals have changed during the COVID-19 pandemic in Zambia. MethodsWe used patient data from Zambias electronic medical record system (SmartCare) for 737 health facilities, representing about 3/4 of all ART patients nationally, to compare the numbers and proportional distributions of patients enrolled in DSD models in the six months before and six months after the first case of COVID-19 was diagnosed in Zambia in March 2020. Segmented linear regression was used to determine whether the introduction of COVID-19 into Zambia further accelerated the increase in DSD scale-up. ResultsBetween September 2019 and August 2020, 181,317 patients aged 15+ (81,520 and 99,797 from September 1, 2019 to March 1, 2020 and from March 1 to August 31, 2020, respectively) enrolled in DSD models in Zambia. Overall participation in all DSD models increased over the study period, but uptake varied by model. The rate of acceleration increased in the second period for home ART delivery (152%), [≤]2-month fast-track (143%), and 3-month MMD (139%). There were significant decelerations in the increase in enrolment for 4-6-month fast-track (-28%) and other models (-19%). ConclusionsParticipation in DSD models for stable ART patients in Zambia increased after the advent of COVID-19, but dispensing intervals diminished. Eliminating obstacles to longer dispensing intervals, including those related to supply chain management, should be prioritized to achieve the expected benefits of DSD models and minimize COVID-19 risk.

Nowcasting and forecasting provincial-level SARS-CoV-2 case positivity using google search data in South Africa (preprint)

Data from non-traditional data sources, such as social media, search engines, and remote sensing, have previously demonstrated utility for disease surveillance. Few studies, however, have focused on countries in Africa, particularly during the SARS-CoV-2 pandemic. In this study, we use searches of COVID-19 symptoms, questions, and at-home remedies submitted to Google to model COVID-19 in South Africa, and assess how well the Google search data forecast short-term COVID-19 trends. Our findings suggest that information seeking trends on COVID-19 could guide models for anticipating COVID-19 trends and coordinating appropriate response measures.

Serological testing in addition to PCR screening for the re-opening of American colleges and universities: potential for cost-savings without compromising pandemic mitigation (preprint)

Importance. The addition of a serological testing could reduce the overall testing costs of a PCR-based SARS-CoV-2 testing reopening plan for colleges/universities in the United States, without compromising the efficacy of the testing plan. Objectives. To determine whether a college/university reopening SARS-CoV-2 testing plan that includes serological testing can be cost-saving compared to a PCR-only testing. Design, Setting, and Participants: We assessed costs of serological testing in addition to PCR testing under various scenarios of university sizes (2000, 10,000, and 40,000) and epidemic conditions (initial antibody prevalence 2.5-15%; cumulative SARS-CoV-2 incidence during the school year 5-30%) of SARS-CoV-2 in the United States. We estimated total testing costs and relative percentage of cost-savings of different screening (i.e. targeted/ universal) and testing (i.e. in-sourcing/out-sourcing) scenarios between September 2020-May 2021. Main Outcomes and Measures: Testing costs of serological testing and PCR testing, Relative percentage of cost saving by including serology testing in addition to PCR testing. Results: Including baseline serology testing alongside routine regular PCR testing can reduce total test volumes and related costs throughout the school year. While the total testing cost is likely much lower if regular PCR testing is insourced compared to outsourced ($5 million vs $34 million for university size 10,000), including serologic testing could achieve the up to 20% cost-savings relative to PCR testing alone. The insourcing of serological testing when PCR testing is insourced can achieve greater cost-savings under high initial antibody prevalence (>5%) and cumulative incidence throughout the school year (>10%) at medium and large sized universities. If PCR testing is outsourced, however, the inclusion of serological testing becomes always preferred in most university sizes and epidemic conditions. Conclusions and Relevance: While regular PCR testing alone is the preferred strategy for containing epidemics, including serology testing may help achieve cost-savings if outbreaks are anticipated, or if baseline seropositivity is high.

Cost-effectiveness of remdesivir and dexamethasone for COVID-19 treatment in South Africa (preprint)

BackgroundSouth Africa recently experienced a first peak in COVID-19 cases and mortality. Dexamethasone and remdesivir both have the potential to reduce COVID-related mortality, but their cost-effectiveness in a resource-limited setting with scant intensive care resources is unknown. MethodsWe projected intensive care unit (ICU) needs and capacity from August 2020 to January 2021 using the South African National COVID-19 Epi Model. We assessed cost-effectiveness of 1) administration of dexamethasone to ventilated patients and remdesivir to non-ventilated patients, 2) dexamethasone alone to both non-ventilated and ventilated patients, 3) remdesivir to non-ventilated patients only, and 4) dexamethasone to ventilated patients only; all relative to a scenario of standard care. We estimated costs from the healthcare system perspective in 2020 USD, deaths averted, and the incremental cost effectiveness ratios of each scenario. ResultsRemdesivir for non-ventilated patients and dexamethasone for ventilated patients was estimated to result in 1,111 deaths averted (assuming a 0-30% efficacy of remdesivir) compared to standard care, and save $11.5 million. The result was driven by the efficacy of the drugs, and the reduction of ICU-time required for patients treated with remdesivir. The scenario of dexamethasone alone to ventilated and non-ventilated patients requires additional $159,000 and averts 1,146 deaths, resulting in $139 per death averted, relative to standard care. ConclusionsThe use of dexamethasone for ventilated and remdesivir for non-ventilated patients is likely to be cost-saving compared to standard care. Given the economic and health benefits of both drugs, efforts to ensure access to these medications is paramount. 40-word summary of articles main pointThe use of remdesivir and dexamethasone for treatment of severe COVID-19 in South Africa is likely to be cost-saving relative to standard care. Enabling access to these medications should be prioritize to improve patient outcomes and reduce total costs.

Population density and basic reproductive number of COVID-19 across United States counties (preprint)

The basic reproductive number (R0) is a function of contact rates among individuals, transmission probability, and duration of infectiousness. We sought to determine the association between population density and R0 of SARS-CoV-2 across U.S. counties, and whether population density could be used as a proxy for contact rates. We conducted a cross-sectional analysis using linear mixed models with random intercept and fixed slopes to assess the association of population density and R0. We also assessed whether this association was differential across county-level main mode of transportation-to-work percentage. Counties with greater population density have greater rates of transmission of SARS-CoV-2, likely due to increased contact rates in areas with greater density. The effect of population density and R0 was not modified by private transportation use. Differential R0 by population density can assist in more accurate predictions of the rate of spread of SARS-CoV-2 in areas that do not yet have active cases.

The role of remdesivir in South Africa: preventing COVID-19 deaths through increasing ICU capacity (preprint)

Countries such as South Africa have limited intensive care unit (ICU) capacity to handle the expected number of COVID-19 patients requiring ICU care. Remdesivir can prevent deaths in countries such as South Africa by decreasing the number of days people spend in ICU, therefore freeing up ICU bed capacity.