HIV testing by public health centers and municipalities, and new HIV cases during the COVID-19 pandemic in Japan

BackgroundDuring the COVID-19 outbreak, medical resources were primarily allocated to COVID-19, which might have reduced facility capacity for HIV testing. Further, people may have opted against HIV testing during this period to avoid COVID-19 exposure. We investigate the influence of the COVID-19 pandemic on HIV testing and its consequences in Japan. MethodsWe analysed quarterly HIV/AIDS-related data from 2015 to the second quarter of 2020 using an anomaly detection approach. The data included the number of consultations that public health centers received, the number of HIV tests performed by public health centers or municipalities, and the number of newly reported HIV cases with and without AIDS diagnosis. As sensitivity analyses, we performed the same analysis for two subgroups: men who have sex with men (MSM) and non-Japanese. FindingsThe number of HIV tests (9,584 vs. 35,908 in the year-before period) and consultations (11,689 vs. 32,565) performed by public health centers significantly declined in the second quarter of 2020, while the proportion of HIV cases with AIDS diagnosis among all HIV cases (36{middle dot}2% vs. 26{middle dot}4%) significantly increased after removing the trend and seasonality effects. The number of HIV cases without AIDS diagnosis numerically decreased (166 vs. 217), although the reduction was not significant. We confirmed similar trend for the MSM and non-Japanese groups. InterpretationThe current HIV testing system including public health centers misses more HIV cases at the early phase of the infection during the pandemic. Given that the clear epidemiological picture of HIV incidence during the pandemic is still uncertain, continuously monitoring the situation as well as securing sufficient test resources using self-test is essential. FundingJapan Society for the Promotion of Science, Japan Science and Technology Agency, Japan Agency for Medical Research and Development. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSBefore this study, we searched PubMed, Medline, and Google Scholar on Oct 12, 2020, for articles investigated the number of HIV test and HIV cases during the COVID-19 pandemic in Japan, using the search terms "novel coronavirus" or "SARS-CoV-2", and "HIV" or "AIDS", and "Japan", with no time restrictions. We found no published work relevant to our study. Added value of this studyDuring the COVID-19 pandemic in Japan, the public health centers and municipalities temporarily suspended facility-based HIV testing to concentrate their limited resources to COVID-19 testing. We investigated the impact of the COVID-19 pandemic on the number of HIV tests in public health centers and municipalities, and on the number of HIV cases with and without AIDS diagnosis. We confirmed that the number of the test declined in the second quarter (April to June) of 2020, and the proportion of HIV with AIDS diagnosis among all HIV cases increased during the same period. Implications of all the available evidenceProviding sufficient HIV testing opportunities even during the pandemic, when facility-based testing is challenging, is necessary for better clinical and public health outcomes. Self-testing and home specimen collection (e.g. dried blood spot or oral fluid test) could be a key to fill the gap between the need for HIV testing and the constraints related to the COVID-19 outbreak.

Estimation of the incubation period of COVID-19 using viral load data

The incubation period, or the time from infection to symptom onset of COVID-19 has been usually estimated using data collected through interviews with cases and their contacts. However, this estimation is influenced by uncertainty in recalling effort of exposure time. We propose a novel method that uses viral load data collected over time since hospitalization, hindcasting the timing of infection with a mathematical model for viral dynamics. As an example, we used the reported viral load data from multiple countries (Singapore, China, Germany, France, and Korea) and estimated the incubation period. The median, 2.5, and 97.5 percentiles of the incubation period were 5.23 days (95% CI: 5.17, 5.25), 3.29 days (3.25, 3.37), and 8.22 days (8.02, 8.46), respectively, which are comparable to the values estimated in previous studies. Using viral load to estimate the incubation period might be a useful approach especially when impractical to directly observe the infection event.

Multidrug treatment with nelfinavir and cepharanthine against COVID-19

Antiviral treatments targeting the emerging coronavirus disease 2019 (COVID-19) are urgently required. We screened a panel of already-approved drugs in a cell culture model of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and identified two new antiviral agents: the HIV protease inhibitor Nelfinavir and the anti-inflammatory drug Cepharanthine. In silico modeling shows Nelfinavir binds the SARS-CoV-2 main protease consistent with its inhibition of viral replication, whilst Cepharanthine inhibits viral attachment and entry into cells. Consistent with their different modes of action, in vitro assays highlight a synergistic effect of this combined treatment to limit SARS-CoV-2 proliferation. Mathematical modeling in vitro antiviral activity coupled with the known pharmacokinetics for these drugs predicts that Nelfinavir will facilitate viral clearance. Combining Nelfinavir/Cepharanthine enhanced their predicted efficacy to control viral proliferation, to ameliorate both the progression of disease and risk of transmission. In summary, this study identifies a new multidrug combination treatment for COVID-19.

Inferring Timing of Infection Using Within-host SARS-CoV-2 Infection Dynamics Model: Are "Imported Cases" Truly Imported?

In countries/communities at risk of future outbreaks of COVID-19, ascertaining whether cases are imported or the result of local secondary transmission is important for government to shape appropriate public health strategies. In this study, we propose a novel approach to identify the timing of infection, whereby we developed a within-host model to capture viral load dynamics post-symptom onset. We submit our approach allow us to differentiate imported cases from local secondary cases. To illustrate our method, we use the initial reported cases in Singapore, where the first reported 18 cases were considered imported, as these individuals had recent travel history to Wuhan, China, which is a hotspot of COVID-19 outbreak. With additional information regarding day of entrance in Singapore, we were able to infer whether these were infected locally or prior to arriving in Singapore. Of all the cases, we identified 6 as likely evidence of ongoing secondary transmission within Singapore. In an early phase of outbreaks, collecting viral load data over time from cases from symptom onset is highly recommended.

Modelling SARS-CoV-2 Dynamics: Implications for Therapy

The scientific community is focussed on developing antiviral therapies to mitigate the impacts of the ongoing novel coronavirus disease (COVID-19) outbreak. This will be facilitated by improved understanding of viral dynamics within infected hosts. Here, using a mathematical model in combination with published viral load data collected from the same specimen (throat / nasal swabs or nasopharyngeal / sputum / tracheal aspirate), we compare within-host dynamics for patients infected in the current outbreak with analogous dynamics for MERS-CoV and SARS-CoV infections. Our quantitative analyses revealed that SARS-CoV-2 infection dynamics are more severe than those for mild cases of MERS-CoV, but are similar to severe cases, and that the viral dynamics of SARS-CoV infection are similar to those of MERS-CoV in mild cases but not in severe case. Consequently, SARS-CoV-2 generates infection dynamics that are more severe than SARS-CoV. Furthermore, we used our viral dynamics model to predict the effectiveness of unlicensed drugs that have different methods of action. The effectiveness was measured by AUC of viral load. Our results indicated that therapies that block de novo infections or virus production are most likely to be effective if initiated before the peak viral load (which occurs around three days after symptom onset on average), but therapies that promote cytotoxicity are likely to have only limited effects. Our unique mathematical approach provides insights into the pathogenesis of SARS-CoV-2 in humans, which are useful for development of antiviral therapies. Significance StatementAntiviral agents with different mechanisms of action have different curative effects depending on precisely when therapy is initiated. Based on a model of viral dynamics, parameterised using viral load data from SARS-CoV-2 infected patients reported by Zou et al. (1), computer simulations were performed. We propose that effective treatment of SARS-CoV-2 infection requires an appropriate choice of class-specific drugs and initiation timing as reported for treatment of other viral infections (2); otherwise, antivirals do not have a significant effect on the within-host viral dynamics of SARS-CoV-2 and are wasted.