Observed and estimated prevalence of Covid-19 in Italy: How to estimate the total cases from medical swabs data

Bayesian sequential approach to monitor COVID-19 variants through test positivity rate from wastewater

Deployment of clinical testing on a massive scale was an essential control measure for curtailing the burden of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections and the magnitude of the COVID-19 (coronavirus disease 2019) pandemic during its waves. As the pandemic progressed, new preventive and surveillance mechanisms emerged. Implementation of vaccine programs, wastewater (WW) surveillance, and at-home COVID-19 antigen tests reduced the demand for mass SARS-CoV-2 testing. Unfortunately, reductions in testing and test reporting rates also reduced the availability of public health data to support decision-making. This paper proposes a sequential Bayesian approach to estimate the COVID-19 test positivity rate (TPR) using SARS-CoV-2 RNA concentrations measured in WW through an adaptive scheme incorporating changes in virus dynamics. The proposed modeling framework was applied to WW surveillance data from two WW treatment plants in California; the City of Davis and the University of California, Davis campus. TPR estimates are used to compute thresholds for WW data using the Centers for Disease Control and Prevention thresholds for low (<5% TPR), moderate (5%-8% TPR), substantial (8%-10% TPR), and high (>10% TPR) transmission. The effective reproductive number estimates are calculated using TPR estimates from the WW data. This approach provides insights into the dynamics of the virus evolution and an analytical framework that combines different data sources to continue monitoring COVID-19 trends. These results can provide public health guidance to reduce the burden of future outbreaks as new variants continue to emerge. IMPORTANCE We propose a statistical model to correlate WW with TPR to monitor COVID-19 trends and to help overcome the limitations of relying only on clinical case detection. We pose an adaptive scheme to model the nonautonomous nature of the prolonged COVID-19 pandemic. The TPR is modeled through a Bayesian sequential approach with a beta regression model using SARS-CoV-2 RNA concentrations measured in WW as a covariable. The resulting model allows us to compute TPR based on WW measurements and incorporates changes in viral transmission dynamics through an adaptive scheme.

Analysis of reporting lag in daily data of COVID-19 in Japan

The daily announcement of positive COVID-19 cases had a major socioeconomic impact. In Japan, it is well known that the characteristic of this number as time series data is the weekly periodicity. We assume that this periodicity is generated by changes in the timing of reporting on the weekend. We analyze a lag structure that shows how congestion that occurs over the weekend affects the number of new confirmed cases at the beginning of the following week. We refer to this reporting delay as the weekend effect. Our study aims to describe the geographical heterogeneity found in the time series of reported positive cases. We use data on the number of new positives reported by the prefectures. Our results suggest that delays generally occur in prefectures with a population of more than 2 million, including Japan's three largest metropolitan areas, Tokyo, Osaka, and Nagoya. The number of new positives was higher in the more populated prefectures. This will explain the weekend effect.

Bayesian sequential approach to monitor COVID-19 variants through positivity rate from wastewater

Trends in COVID-19 infection have changed throughout the pandemic due to myriad factors, including changes in transmission driven by social behavior, vaccine development and uptake, mutations in the virus genome, and public health policies. Mass testing was an essential control measure for curtailing the burden of COVID-19 and monitoring the magnitude of the pandemic during its multiple phases. However, as the pandemic progressed, new preventive and surveillance mechanisms emerged. Implementing vaccine programs, wastewater (WW) surveillance, and at-home COVID-19 tests reduced the demand for mass severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) testing. This paper proposes a sequential Bayesian approach to estimate the COVID-19 positivity rate (PR) using SARS-CoV-2 RNA concentrations measured in WW through an adaptive scheme incorporating changes in virus dynamics. PR estimates are used to compute thresholds for WW data using the CDC thresholds for low, substantial, and high transmission. The effective reproductive number estimates are calculated using PR estimates from the WW data. This approach provides insights into the dynamics of the virus evolution and an analytical framework that combines different data sources to continue monitoring the COVID-19 trends. These results can provide public health guidance to reduce the burden of future outbreaks as new variants continue to emerge. The proposed modeling framework was applied to the City of Davis and the campus of the University of California Davis.

The Italian COVID-19 Anxiety Syndrome Scale: Investigation of the COVID-19 anxiety syndrome and its association with psychological symptoms in an Italian population

INTRODUCTION

The COVID-19 Anxiety Syndrome Scale (C-19ASS) is a quick and reliable scale assessing dysfunctional coping strategies activated in response to COVID-19 fear and threat. The present study aimed to provide a preliminary validation of the Italian version of the C-19ASS and investigated whether the C-19ASS would mediate the relationship between the Big Five personality traits and psychological outcomes.

METHOD

In Study 1, a community sample of 271 participants completed the Italian version of the C-19ASS and results were subjected to a Principal Component Analysis. In study 2, a community sample of 484 participants completed the Italian version of the C-19ASS and a series of measures assessing COVID-19 anxiety, COVID-19 fear, functional impairment, personality traits, depression, generalized anxiety and health anxiety. Internal consistency, concurrent and incremental validity were assessed. Path analyses were run.

RESULTS

Factor analysis identified a two-factor solution (i.e., C-19ASS Perseveration and C-19ASS Avoidance) and confirmatory factor analysis suggested a two-factor model best fits the data. The Italian version of the C-19ASS showed good internal consistency. There was also evidence of convergent validity and incremental validity. Path analyses showed that C-19ASS Perseveration mediates the relationship between emotional stability and psychological symptoms (depression, generalized anxiety and health anxiety).

CONCLUSION

The Italian version of the C-19ASS appears to be a reliable and valid measure of the COVID-19 anxiety syndrome. The COVID-19 anxiety syndrome could be a suitable therapeutic target to reduce psychological symptoms typically linked to pandemic events, such as depression generalized anxiety and health anxiety.

Estimating the infection burden of COVID-19 in Malaysia

Malaysia has reported 2.75 million cases and 31,485 deaths as of 30 December 2021. Underestimation remains an issue due to the underdiagnosis of mild and asymptomatic cases. We aimed to estimate the burden of COVID-19 cases in Malaysia based on an adjusted case fatality rate (aCFR). Data on reported cases and mortalities were collated from the Ministry of Health official GitHub between 1 March 2020 and 30 December 2021. We estimated the total and age-stratified monthly incidence rates, mortality rates, and aCFR. Estimated new infections were inferred from the age-stratified aCFR. The total estimated infections between 1 March 2020 and 30 December 2021 was 9,955,000-cases (95% CI: 6,626,000-18,985,000). The proportion of COVID-19 infections in ages 0-11, 12-17, 18-50, 51-65, and above 65 years were 19.9% (n = 1,982,000), 2.4% (n = 236,000), 66.1% (n = 6,577,000), 9.1% (n = 901,000), 2.6% (n = 256,000), respectively. Approximately 32.8% of the total population in Malaysia was estimated to have been infected with COVID-19 by the end of December 2021. These estimations highlight a more accurate infection burden in Malaysia. It provides the first national-level prevalence estimates in Malaysia that adjusted for underdiagnosis. Naturally acquired community immunity has increased, but approximately 68.1% of the population remains susceptible. Population estimates of the infection burden are critical to determine the need for booster doses and calibration of public health measures.

Development of Approaches and Metrics to Measure the Impact and Improve the Clinical Outcomes of Patients With Frailty in the Era of COVID-19. The COMETA Italian Protocol

The outbreak of the coronavirus 2 disease 2019 (COVID-19) puts an enormous burden on healthcare systems worldwide. This may worsen outcomes in patients with severe chronic diseases such as cancer, autoimmune diseases, and immune deficiencies. In this critical situation, only a few available data exist, which do not allow us to provide practical guides for the treatment of oncological or immunocompromised patients. Therefore, a further step forward is needed, addressing the specific needs and demands of frail patients in the pandemic era. Here we aim to present a protocol of a study approved by an ethical committee named "CO.M.E.TA". CO.M.E.TA protocol is a network project involving six Italian institutions and its goals are: i) to measure and compare the impact of the pandemic on the access of cancer and immunocompromised patients to therapies in three Italian regions; ii) to assess how reorganizational measures put in place in these different institutions have impacted specific metrics of performance; iii) to establish a COVID-19 Biobank of biological samples from SARS-CoV-2 infected patients to be used to study immunological alterations in patients with immune frailty.

Determinants of SARS-CoV-2 Infection in the Older Adult Population: Data from the LOST in Lombardia Study

Most COVID-19 fatalities have occurred among older adults; however, evidence regarding the determinants of SARS-CoV-2 infection in this population is limited. Telephone interviews were conducted in November 2020 with a representative sample of 4400 Italians aged ≥65 years from the Lombardy region. We determined the prevalence of a history of SARS-CoV-2 infection. Through unconditional multiple logistic regression models, we estimated the odds ratios (ORs) of infection and the corresponding 95% confidence intervals (CIs). We further evaluated whether infection was related to a reduction in mental wellbeing. Of the participants, 4.9% reported a previous infection. No significant relationship between sex and infection was observed. Prior infection was less frequently reported in subjects aged ≥70 (OR = 0.55; 95% CI: 0.41–0.74) compared to 65–69 years, with no trend after 70 years of age. Those with at least one chronic condition reported a lower infection rate compared to healthy subjects (OR = 0.68; 95% CI: 0.49–0.93). Participants who lived alone more frequently reported infection than those who cohabited (OR = 2.33; 95% CI: 1.29–4.20). Prior infection was related to increased depressive symptoms (OR = 1.57; 95% CI: 1.17–2.10). This representative study of people aged ≥65 years suggests that in Italy, the oldest subjects and chronic patients less frequently exposed themselves to SARS-CoV-2 infection.

Inheritance of a common androgen synthesis variant allele is associated with female COVID susceptibility in UK Biobank

Context

A sex discordance in COVID exists, with males disproportionately affected. Although sex steroids may play a role in this discordance, no definitive genetic data exist to support androgen-mediated immune suppression neither for viral susceptibility nor for adrenally produced androgens.

Objective

The common adrenal-permissive missense-encoding variant HSD3B1(1245C) that enables androgen synthesis from adrenal precursors and that has been linked to suppression of inflammation in severe asthma was investigated in COVID susceptibility and outcomes reported in the UK Biobank.

Methods

The UK Biobank is a long-term study with detailed medical information and health outcomes for over 500 000 genotyped individuals. We obtained COVID test results, inpatient hospital records, and death records and tested for associations between COVID susceptibility or outcomes and HSD3B1(1245A/C) genotype. Primary analyses were performed on the UK Biobank Caucasian cohort. The outcomes were identification as a COVID case among all subjects, COVID positivity among COVID-tested subjects, and mortality among subjects identified as COVID cases.

Results

Adrenal-permissive HSD3B1(1245C) genotype was associated with identification as a COVID case (odds ratio (OR): 1.11 per C allele, 95% CI: 1.04-1.18, P = 0.0013) and COVID-test positivity (OR: 1.09, 95% CI: 1.02-1.17, P = 0.011) in older (≥70 years of age) women. In women identified as COVID cases, there was a positive linear relationship between age and 1245C allele frequency (P < 0.0001). No associations were found between genotype and mortality or between genotype and circulating sex hormone levels.

Conclusion

Our study suggests that a common androgen synthesis variant regulates immune susceptibility to COVID infection in women, with increasingly strong effects as women age.

Investigation of COVID-19 infection in subjects with Klinefelter syndrome

PURPOSE

COVID-19 has worse clinical outcomes in males compared with females and testosterone may determine gender differences. Hypogonadism and supernumerary X chromosome may have a role in the SARS-CoV-2 infection in Klinefelter syndrome (KS). Aim of the study was evaluating COVID-19 frequency and severity in KS.

METHODS

Participants were invited to complete a retrospective self-administered questionnaire containing multiple choice and open-ended answers.

RESULTS

COVID-19 was detected in 10% of the evaluated KS subjects; none was hospitalized. 44.4% of COVID-19 patients had one cohabitant-infected versus 3% of non-infected (p < 0.01). Testosterone levels in infected patients were lower compared to those of non-infected subjects (3.1 ± 1.2 ng/ml vs. 5.2 ± 2 ng/ml, p < 0.05).

CONCLUSIONS

The frequency of SARS-CoV-2 infection among KS subjects was 10%. All infected patients showed mild symptoms. The presence of one affected cohabitant significantly associated with SARS-CoV-2 infection. An association between SARS-CoV-2 and hypogonadism was confirmed.

The COVID-19 Pandemic Impact on the Outcome of Medically Assisted Reproduction Pregnancies

Background

The impact of the Coronavirus Disease-2019 (COVID-19) pandemic on pregnancy is not well-understood. During the outbreak, the initial approach suggested by the major societies was to postpone all non-urgent assisted reproductive technology (ART) treatments. Nevertheless, the Italian Society of Fertility and Sterility and Reproductive Medicine considered ethically correct to proceed with ART treatments, as the infertility rate is increasing over time, with a consistent decline in the live birth rate. The objective of our study was to assess the impact of the COVID-19 pandemic on the outcomes of ART pregnancies, in terms of early pregnancy loss, overall success rate, and live birth rate.

Methods

We conducted a single-center retro-prospective cohort study. Patients who underwent ART treatments from 1 March 2020 to 28 February 2021 (pandemic ART cohort, pART; n = 749) and from 1 March 2019 to 29 February 2020 (control cohort, CTR; n = 844) were enrolled. The study had a duration of 24 months. Patients underwent baseline severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) nasopharyngeal swab; quantitative serum beta human chorionic gonadotropin (β-hCG) to assess pregnancy; pelvic transvaginal ultrasound; and follow-up until delivery. The study took place at the ART Center of the University Hospital in Florence, Italy.

Results

There were not statistically significant differences on implantation rate (pART 0.348 ± 0.034 vs. CTR 0.365 ± 0.033, CI = 95%, p = 0.49), clinical pregnancy rate (pART 0.847 ± 0.044 vs. CTR 0.864 ± 0.038, CI = 95%, p = 0.56), and ectopic pregnancy rate (pART 0.008 ± 0.011 vs. CTR 0.01 ± 0.011, CI = 95%, p = 0.79). Neither first trimester miscarriage rate was different between the groups (pART 0.224 ± 0.056 vs. CTR 0.213 ± 0.05, CI = 95%, p = 0.77) nor second trimester miscarriage rate (pART 0.018 ± 0.018 vs. CTR 0.019 ± 0.017, CI = 95%, p = 0.95). Live birth rate remained unchanged during the pandemic (pART 0.22 ± 0.03 vs. CTR 0.239 ± 0.029, CI = 95%, p = 0.37) and stable even when compared to our center rate between 2015 and 2019 (pART 0.222 ± 0.03 vs. general rate 0.224 ± 0.014, CI = 95%, p = 0.83).

Conclusion

The COVID-19 pandemic did not cause a statistically significant change in the live birth rate and in the pregnancy loss rate. ART during the COVID-19 pandemic can be considered fair and safe, ethically and medically appropriate. Patients and physicians should be reassured that ART pregnancy outcomes do not seem to be jeopardized by the pandemic state.

Diffusion of COVID-19 among children and adolescents during the second and third waves of the pandemic in Italy

This paper explores COVID-19 diffusion among children and adolescents (up to 19 years old) in Italy using the publicly available data that were collected and released by the Italian National Institute of Health (ISS). We consider in more detail the so-called second and third waves of the pandemic in Italy and explore the relationship between schools opening and the diffusion of COVID-19, which is a highly debated topic in the recent reference literature. We analyse the dynamics of COVID-19 incidence in the country as a whole and in its individual regions. Moreover, we compare the regions in which different levels of restrictions were imposed during the pandemic as well as different school closure calendars. We found there to be a significant correlation between the dynamics of the COVID-19 infections among young people in Italy and school closures during both the second and the third waves of the pandemic.

CONCLUSION

Specifically, we found school closures to have mitigated the spread of the infection, especially among patients between the ages of 14 and 19.

WHAT IS KNOWN

• The relationship between the opening of schools and the diffusion of COVID-19 is a debated topic. • SARS-CoV-2 diffusion among school-aged adolescents is almost twice as that among children. • SARS-CoV-2 is a mild disease for infants and children.

WHAT IS NEW

• We analysed original data on the diffusion of COVID-19 among children and adolescents in Italy. • We calculated incidence of COVID-19 with reference to school-age classes and compared over time in the whole country and in the regions of Italy. • We analysed incidence dynamics considering school closures and other restrictions imposed by the local and national authorities to limit virus diffusion.

Heterogeneous Longitudinal Antibody Responses to Covid-19 mRNA Vaccination

Background

Public health measures to stem the coronavirus disease 2019 (COVID-19) pandemic are challenged by social, economic, health status, and cultural disparities that facilitate disease transmission and amplify its severity. Prior pre-clinical biomedical technologic advances in nucleic acid-based vaccination enabled unprecedented speed of conceptualization, development, production, and widespread distribution of mRNA vaccines that target SARS-CoV-2's Spike (S) protein.

Design

Twenty-five female and male volunteer fulltime employees at the Providence VA Medical Center participated in this study to examine longitudinal antibody responses to the Moderna mRNA-1273 vaccine. IgM-S and IgG-S were measured in serum using the Abbott IgM-S-Qualitative and IgG2-S-Quantitative chemiluminescent assays.

Results

Peak IgM responses after Vaccine Dose #1 were delayed in 6 (24%) and absent in 7 (28%) participants. IgG2-S peak responses primarily occurred 40 to 44 days after Vaccine Dose #1, which was also 11 to 14 days after Vaccine Dose #2. However, subgroups exhibited Strong (n = 6; 24%), Normal (n = 13; 52%), or Weak (n = 6; 24%) peak level responses that differed significantly from each other (P < .005 or better). The post-peak IgG2-S levels declined progressively, and within 6 months reached the mean level measured 1 month after Vaccine Dose #1. Weak responders exhibited persistently low levels of IgG2-S. Variability in vaccine responsiveness was unrelated to age or gender.

Conclusion

Host responses to SARS-CoV-2-Spike mRNA vaccines vary in magnitude, duration and occurrence. This study raises concern about the lack of vaccine protection in as many as 8% of otherwise normal people, and the need for open dialog about future re-boosting requirements to ensure long-lasting immunity via mRNA vaccination versus natural infection.

Caring for nursing home residents with COVID-19: a "hospital-at-nursing home" intermediate care intervention

Background

Nursing home (NH) residents have been dramatically affected by COVID-19, with extremely high rates of hospitalization and mortality.

Aims

To describe the features and impact of an assistance model involving an intermediate care mobile medical specialist team (GIROT, Gruppo Intervento Rapido Ospedale Territorio) aimed at delivering “hospital-at-nursing home” care to NH residents with COVID-19 in Florence, Italy.

Methods

The GIROT activity was set-up during the first wave of the pandemic (W1, March–April 2020) and became a structured healthcare model during the second (W2, October 2020–January 2021). The activity involved (1) infection transmission control among NHs residents and staff, (2) comprehensive geriatric assessment including prognostication and geriatric syndromes management, (3) on-site diagnostic assessment and protocol-based treatment of COVID-19, (4) supply of nursing personnel to understaffed NHs. To estimate the impact of the GIROT intervention, we reported hospitalization and infection lethality rates recorded in SARS-CoV-2-positive NH residents during W1 and W2.

Results

The GIROT activity involved 21 NHs (1159 residents) and 43 NHs (2448 residents) during W1 and W2, respectively. The percentage of infected residents was higher in W2 than in W1 (64.5% vs. 38.8%), while both hospitalization and lethality rates significantly decreased in W2 compared to W1 (10.1% vs 58.2% and 23.4% vs 31.1%, respectively).

Discussion

Potentiating on-site care in the NHs paralleled a decrease of hospital admissions with no increase of lethality.

Conclusions

An innovative “hospital-at-nursing home” patient-centred care model based on comprehensive geriatric assessment may provide a valuable contribution in fighting COVID-19 in NH residents.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40520-021-01959-z.

Underdetection in a stochastic SIR model for the analysis of the COVID-19 Italian epidemic

We propose a way to model the underdetection of infected and removed individuals in a compartmental model for estimating the COVID-19 epidemic. The proposed approach is demonstrated on a stochastic SIR model, specified as a system of stochastic differential equations, to analyse data from the Italian COVID-19 epidemic. We find that a correct assessment of the amount of underdetection is important to obtain reliable estimates of the critical model parameters. The adaptation of the model in each time interval between relevant government decrees implementing contagion mitigation measures provides short-term predictions and a continuously updated assessment of the basic reproduction number.

Modelling SARS-CoV-2 unreported cases in Italy: Analysis of serological survey and vaccination scenarios

OBJECTIVES

Aim of the present paper is the study of the large unreported component, characterizing the SARS-CoV-2 epidemic event in Italy, taking advantage of the Istat survey. Particular attention is devoted to the sensitivity and specificity of the serological test and their effects.

METHODS

The model satisfactory reproduces the data of the Italian survey showing a relevant predictive power and relegating in a secondary position models which do not include, in the simulation, the presence of asymptomatic groups. The corrections due to the serological test sensitivity (in particular those ones depending on the symptoms onset) are crucial for a realistic analysis of the unreported (and asymptomatic) components.

RESULTS

The relevant presence of an unreported component during the second pandemic wave in Italy is confirmed and the ratio of reported to unreported cases is predicted to be roughly 1:4 in the last months of year 2020. A method to correct the serological data on the basis of the antibody sensitivity is suggested and systematically applied. The asymptomatic component is also studied in some detail and its amount quantified. A model analyses of the vaccination scenarios is performed confirming the relevance of a massive campaign (at least 80000 immunized per day) during the first six months of the year 2021, to obtain important immunization effects within August/September 2021.

Lies, Gosh Darn Lies, and not enough good statistics: why epidemic model parameter estimation fails

We sought to investigate whether epidemiological parameters that define epidemic models could be determined from the epidemic trajectory of infections, recovery, and hospitalizations prior to peak, and also to evaluate the comparability of data between jurisdictions reporting their statistics. We found that, analytically, the pre-peak growth of an epidemic underdetermines the model variates, and that the rate limiting variables are dominated by the exponentially expanding eigenmode of their equations. The variates quickly converge to the ratio of eigenvector components of the positive growth mode, which determines the doubling time. Without a sound epidemiological study framework, measurements of infection rates and other parameters are highly corrupted by uneven testing rates, uneven counting, and under reporting of relevant values. We argue that structured experiments must be performed to estimate these parameters in order to perform genetic association studies, or to construct viable models accurately predicting critical quantities such as hospitalization loads.

A Spatio-temporal analysis of COVID-19 outbreak in Italy

Within two weeks from the first detection of the SARS-CoV-2 positive patient on 21 February, from Lombardy the disease has spread over every region in Italy. The main objective of this study is to identify spatial effects and spatiotemporal patterns of the outbreak of COVID-19 in different regions of Italy. Spatial indicators for different periods, as Moran's I, local Moran, LISA clusters, Getis and Ord G, and scatterplots are used for this purpose. Results confirm the great presence of spatial effects as well as changes in spatial regimes between the quarantine and the easing phase. The evidence could be of help for policy-makers to a proper assessments of health strategies aware of local characteristics.

Prevalence and impact of COVID-19 in Parkinson's disease: evidence from a multi-center survey in Tuscany region

Background

If Parkinson’s Disease (PD) may represent a risk factor for Coronavirus disease 2019 (COVID-19) is debated and there are few data on the direct and indirect effects of this pandemic in PD patients.

Objective

In the current study we evaluated the prevalence, mortality and case-fatality of COVID-19 in a PD cohort, also exploring possible risk factors. We also aimed to investigate the effect of lockdown on motor/non-motor symptoms in PD patients as well as their acceptability/accessibility to telemedicine.

Method

A case-controlled survey about COVID-19 and other clinical features in PD patients living in Tuscany was conducted. In non-COVID-19 PD patients motor/non-motor symptoms subjective worsening during the lockdown as well as feasibility of telemedicine were explored.

Results

Out of 740 PD patients interviewed, 7 (0.9%) were affected by COVID-19, with 0.13% mortality and 14% case-fatality. COVID-19 PD patients presented a higher presence of hypertension (p < 0.001) and diabetes (p = 0.049) compared to non-COVID-19. In non-COVID-19 PD population (n = 733) about 70% did not experience a subjective worsening of motor symptoms or mood, anxiety or insomnia. In our population 75.2% of patients was favorable to use technology to perform scheduled visits, however facilities for telemedicine were available only for 51.2% of cases.

Conclusion

A higher prevalence of COVID-19 respect to prevalence in Tuscany and Italy was found in the PD population. Hypertension and diabetes, as for general population, were identified as risk factors for COVID-19 in PD. PD patients did not experience a subjective worsening of symptoms during lockdown period and they were also favorable to telemedicine, albeit we reported a reduced availability to perform it.