A Bayesian approach to estimating COVID-19 incidence and infection fatality rates.

Naive estimates of incidence and infection fatality rates (IFR) of coronavirus disease 2019 suffer from a variety of biases, many of which relate to preferential testing. This has motivated epidemiologists from around the globe to conduct serosurveys that measure the immunity of individuals by testing for the presence of SARS-CoV-2 antibodies in the blood. These quantitative measures (titer values) are then used as a proxy for previous or current infection. However, statistical methods that use this data to its full potential have yet to be developed. Previous researchers have discretized these continuous values, discarding potentially useful information. In this article, we demonstrate how multivariate mixture models can be used in combination with post-stratification to estimate cumulative incidence and IFR in an approximate Bayesian framework without discretization. In doing so, we account for uncertainty from both the estimated number of infections and incomplete deaths data to provide estimates of IFR. This method is demonstrated using data from the Action to Beat Coronavirus erosurvey in Canada.

The evolution of SARS-CoV-2 seroprevalence in Canada: a time-series study, 2020-2023.

BACKGROUND: During the first year of the COVID-19 pandemic, the proportion of reported cases of COVID-19 among Canadians was under 6%. Although high vaccine coverage was achieved in Canada by fall 2021, the Omicron variant caused unprecedented numbers of infections, overwhelming testing capacity and making it difficult to quantify the trajectory of population immunity. METHODS: Using a time-series approach and data from more than 900 000 samples collected by 7 research studies collaborating with the COVID-19 Immunity Task Force (CITF), we estimated trends in SARS-CoV-2 seroprevalence owing to infection and vaccination for the Canadian population over 3 intervals: prevaccination (March to November 2020), vaccine roll-out (December 2020 to November 2021), and the arrival of the Omicron variant (December 2021 to March 2023). We also estimated seroprevalence by geographical region and age. RESULTS: By November 2021, 9.0% (95% credible interval [CrI] 7.3%-11%) of people in Canada had humoral immunity to SARS-CoV-2 from an infection. Seroprevalence increased rapidly after the arrival of the Omicron variant - by Mar. 15, 2023, 76% (95% CrI 74%-79%) of the population had detectable antibodies from infections. The rapid rise in infection-induced antibodies occurred across Canada and was most pronounced in younger age groups and in the Western provinces: Manitoba, Saskatchewan, Alberta and British Columbia. INTERPRETATION: Data up to March 2023 indicate that most people in Canada had acquired antibodies against SARS-CoV-2 through natural infection and vaccination. However, given variations in population seropositivity by age and geography, the potential for waning antibody levels, and new variants that may escape immunity, public health policy and clinical decisions should be tailored to local patterns of population immunity.

Unilateral and bilateral MRI-targeted repetitive transcranial magnetic stimulation for treatment-resistant depression: a randomized controlled study.

BACKGROUND: Several factors may mitigate the efficacy of repetitive transcranial magnetic stimulation (rTMS) over sham rTMS in patients with treatment-resistant depression (TRD). These factors include unilateral stimulation (i.e., treatment of only the left dorsolateral prefrontal cortex [DLPFC]), suboptimal methods of targeting the DLPFC and insufficient stimulation intensity (based on coil-to-cortex distance). METHODS: We recruited patients with TRD between the ages of 18 and 85 years from a university hospital, and participants were randomized to receive sequential bilateral rTMS (600 pulses at 1 Hz followed by 1500 pulses at 10 Hz), unilateral high-frequency left (HFL)-rTMS (2100 pulses at 10 Hz) or sham rTMS for 3 or 6 weeks depending on treatment response. Stimulation was targeted with MRI localization over the junction of the middle and anterior thirds of the middle frontal gyrus, using 120% of the coil-to-cortex adjusted motor threshold. Our primary outcome of interest was the remission rate. RESULTS: A total of 121 patients participated in this study. The remission rate was significantly higher in the bilateral group than the sham group. The remission rate in the HFL-rTMS group was intermediate and did not differ statistically from the rate in the 2 other groups. There were no significant differences in reduction of depression scores among the 3 groups. LIMITATIONS: The number of pulses used per session in the unilateral group was somewhat lower in our trial than in more recent trials, and the sham condition did not involve active stimulation. CONCLUSION: Our findings suggest that sequential bilateral rTMS is superior to sham rTMS; however, adjusting for coil-to-cortex distance did not yield enhanced efficacy rates.

Geo-spatial factors associated with infection risk among young children in rural Ghana: a secondary spatial analysis.

BACKGROUND: Determining the spatial patterns of infection among young children living in a malaria-endemic area may provide a means of locating high-risk populations who could benefit from additional resources for treatment and improved access to healthcare. The objective of this secondary analysis of baseline data from a cluster-randomized trial among 1943 young Ghanaian children (6-35 months of age) was to determine the geo-spatial factors associated with malaria and non-malaria infection status. METHODS: Spatial analyses were conducted using a generalized linear geostatistical model with a Matern spatial correlation function and four definitions of infection status using different combinations of inflammation (C-reactive protein, CRP > 5 mg/L) and malaria parasitaemia (with or without fever). Potentially informative variables were included in a final model through a series of modelling steps, including: individual-level variables (Model 1); household-level variables (Model 2); and, satellite-derived spatial variables (Model 3). A final (Model 4) and maximal model (Model 5) included a set of selected covariates from Models 1 to 3. RESULTS: The final models indicated that children with inflammation (CRP > 5 mg/L) and/or any evidence of malaria parasitaemia at baseline were more likely to be under 2 years of age, stunted, wasted, live further from a health facility, live at a lower elevation, have less educated mothers, and higher ferritin concentrations (corrected for inflammation) compared to children without inflammation or parasitaemia. Similar results were found when infection was defined as clinical malaria or parasitaemia with/without fever (definitions 3 and 4). Conversely, when infection was defined using CRP only, all covariates were non-significant with the exception of baseline ferritin concentration. In Model 5, all infection definitions that included parasitaemia demonstrated a significant interaction between normalized difference vegetation index and land cover type. Maps of the predicted infection probabilities and spatial random effect showed defined high- and low-risk areas that tended to coincide with elevation and cluster around villages. CONCLUSIONS: The risk of infection among young children in a malaria-endemic area may have a predictable spatial pattern which is associated with geographical characteristics, such as elevation and distance to a health facility. Original trial registration clinicaltrials.gov (NCT01001871).

Proprotein convertase subtilisin kexin type 9 promotes intestinal overproduction of triglyceride-rich apolipoprotein B lipoproteins through both low-density lipoprotein receptor-dependent and -independent mechanisms.

BACKGROUND: Proprotein convertase subtilisin kexin type 9 (PCSK9) promotes the degradation of the low-density lipoprotein (LDL) receptor (LDLR), and its deficiency in humans results in low plasma LDL cholesterol and protection against coronary heart disease. Recent evidence indicates that PCSK9 also modulates the metabolism of triglyceride-rich apolipoprotein B (apoB) lipoproteins, another important coronary heart disease risk factor. Here, we studied the effects of physiological levels of PCSK9 on intestinal triglyceride-rich apoB lipoprotein production and elucidated for the first time the cellular and molecular mechanisms involved. METHODS AND RESULTS: Treatment of human enterocytes (CaCo-2 cells) with recombinant human PCSK9 (10 µg/mL for 24 hours) increased cellular and secreted apoB48 and apoB100 by 40% to 55% each (P<0.01 versus untreated cells), whereas short-term deletion of PCSK9 expression reversed this effect. PCSK9 stimulation of apoB was due to a 1.5-fold increase in apoB mRNA (P<0.01) and to enhanced apoB protein stability through both LDLR-dependent and LDLR-independent mechanisms. PCSK9 decreased LDLR protein (P<0.01) and increased cellular apoB stability via activation of microsomal triglyceride transfer protein. PCSK9 also increased levels of the lipid-generating enzymes FAS, SCD, and DGAT2 (P<0.05). In mice, human PCSK9 at physiological levels increased intestinal microsomal triglyceride transfer protein levels and activity regardless of LDLR expression. CONCLUSIONS: PCSK9 markedly increases intestinal triglyceride-rich apoB production through mechanisms mediated in part by transcriptional effects on apoB, microsomal triglyceride transfer protein, and lipogenic genes and in part by posttranscriptional effects on the LDLR and microsomal triglyceride transfer protein. These findings indicate that targeted PCSK9-based therapies may also be effective in the management of postprandial hypertriglyceridemia.

Excess deaths in China during SARS-CoV-2 viral waves in 2022-2023.

Background: The extent to which the Omicron variant of SARS-CoV-2 raised death rates in China during its viral wave of December 2022-January 2023 remains largely undocumented. Methods: We worked with an established national survey organization to survey 8,004 adults in all 31 administrative areas of China to ask about deaths in families since January 2020. We examined age-specific death rates, focusing on deaths above age 60 years, and at 15-59 years. We compared these to the United Nations (UN) estimates of age-specific mortality in 2019. Findings: The survey participants were broadly similar to the 2020 census and other national surveys in age, sex, region, and smoking status, but had lower SARS-CoV-2 vaccination rates and higher education levels. There were no differences in reporting of deaths during the Omicron period (after November 2021) versus earlier. The survey captured 456 deaths, of which 329 occurred at ages 60+ years and 212 were of women. At ages 60+ years, death rates approximately doubled during December 2022-January 2023. Deaths at ages 15-59 years did not rise appreciably. The UN estimates approximately 675,000 deaths per month at ages 60+ years in 2019. If rates doubled nationally as in our survey, China had approximately 1.35 million excess deaths from December 2022-January 2023. Interpretation: China experienced a sharp but short increase in excess deaths among its elderly during the Omicron wave. If death registry data corroborate our estimates of substantial excess deaths in China, the worldwide estimates of excess deaths due to SARS-CoV-2 in 2022-2023 may need upward adjustment.

Smoking Cessation and Short- and Longer-Term Mortality.

BACKGROUND: Smoking cessation reduces mortality and morbidity. However, the extent and rapidity at which cessation reduces contemporary death rates from smoking-related illnesses remain uncertain. METHODS: We pooled current or former versus never cigarette smoker hazard ratios from four national cohorts with linkage to death registries in the United States, United Kingdom, Norway, and Canada among adults 20 to 79 years of age from 1974 to 2018. We calculated excess risk differences and survival, comparing current or never smokers with age-specific cessation and cessation fewer than 3, 3 to 9, or 10 or more years earlier. RESULTS: Among 1.48 million adults followed for 15 years, 122,697 deaths occurred. Adjusting for age, education, alcohol use, and obesity, current smokers had higher hazard ratios for death compared with never smokers (2.8 for women, 2.7 for men). Survival between 40 and 79 years of age was 12 and 13 years less in women and men, respectively, who smoked compared with never smokers (about 24 to 26 years of life lost for smokers who died from smoking combined with zero loss for smokers who did not die from smoking). Former smokers showed lower hazard ratios (1.3 in both women and men). Short-term cessation for fewer than 3 years was associated with a lower excess risk of 95% in women and 90% in men younger than 40 years of age, with notable beneficial associations also in women and men 40 to 49 years of age (81% and 61%, respectively) and 50 to 59 years of age (63% and 54%, respectively). Cessation at every age was associated with longer survival, particularly cessation before 40 years of age. Among all ages and compared with continued smoking, cessation of fewer than 3 years potentially averted 5 years of life lost and cessation for 10 or more years averted about 10 years of life lost, yielding survival similar to that of never smokers. CONCLUSIONS: Quitting smoking at any age, but particularly in younger years, was associated with lower excess mortality overall and from vascular, respiratory, and neoplastic diseases. Beneficial associations were evident as early as 3 years after cessation. (Funded by Canadian Institutes of Health Research [FDN-154277].)

Hybrid immunity from SARS-CoV-2 infection and vaccination in Canadian adults: cohort study.

Background: Few national-level studies have evaluated the impact of 'hybrid' immunity (vaccination coupled with recovery from infection) from the Omicron variants of SARS-CoV-2.Methods: From May 2020 to December 2022, we conducted serial assessments (each of ~4000-9000 adults) examining SARS-CoV-2 antibodies within a mostly representative Canadian cohort drawn from a national online polling platform. Adults, most of whom were vaccinated, reported viral test-confirmed infections and mailed self-collected dried blood spots to a central lab. Samples underwent highly sensitive and specific antibody assays to spike and nucleocapsid protein antigens, the latter triggered only by infection. We estimated cumulative SARS-CoV-2 incidence prior to the Omicron period and during the BA.1/1.1 and BA.2/5 waves. We assessed changes in antibody levels and in age-specific active immunity levels.Results: Spike levels were higher in infected than in uninfected adults, regardless of vaccination doses. Among adults vaccinated at least thrice and infected more than six months earlier, spike levels fell notably and continuously for the nine months post-vaccination. By contrast, among adults infected within six months, spike levels declined gradually. Declines were similar by sex, age group, and ethnicity. Recent vaccination attenuated declines in spike levels from older infections. In a convenience sample, spike antibody and cellular responses were correlated. Near the end of 2022, about 35% of adults above age 60 had their last vaccine dose more than six months ago, and about 25% remained uninfected. The cumulative incidence of SARS-CoV-2 infection rose from 13% (95% CI 11-14%) before omicron to 78% (76-80%) by December 2022, equating to 25 million infected adults cumulatively. However, the COVID-19 weekly death rate during the BA.2/5 waves was less than half of that during the BA.1/1.1 wave, implying a protective role for hybrid immunity.Conclusions: Strategies to maintain population-level hybrid immunity require up-to-date vaccination coverage, including among those recovering from infection. Population-based, self-collected dried blood spots are a practicable biological surveillance platform.Funding: Funding was provided by the COVID-19 Immunity Task Force, Canadian Institutes of Health Research, Pfizer Global Medical Grants, and St. Michael's Hospital Foundation. PJ and ACG are funded by the Canada Research Chairs Program.

PCR Test Positivity and Viral Loads during Three SARS-CoV-2 Viral Waves in Mumbai, India.

SARS-CoV-2 polymerase chain reaction (PCR) tests generally report only binary (positive or negative) outcomes. Quantitative PCR tests can provide epidemiological information on viral transmission patterns in populations. SARS-CoV-2 transmission patterns during India's SARS-CoV-2 viral waves remain largely undocumented. We analyzed 2.7 million real-time PCR testing records collected in Mumbai, a bellwether for other Indian cities. We used the inverse of cycle threshold (Ct) values to determine the community-level viral load. We quantified wave-specific differences by age, sex, and slum population density. Overall, PCR positivity was 3.4% during non-outbreak periods, rising to 23.2% and 42.8% during the original (June-November 2020) and Omicron waves (January 2022), respectively, but was a surprisingly low 9.9% during the Delta wave (March-June 2021; which had the largest increase in COVID deaths). The community-level median Ct values fell and rose ~7-14 days prior to PCR positivity rates. Viral loads were four-fold higher during the Delta and Omicron waves than during non-outbreak months. The Delta wave had high viral loads at older ages, in women, and in areas of higher slum density. During the Omicron wave, differences in viral load by sex and slum density had disappeared, but older adults continued to show a higher viral load. Mumbai's viral waves had markedly high viral loads representing an early signal of the pandemic trajectory. Ct values are practicable monitoring tools.

The Nova Scotia Community Cancer Matrix: A geospatial tool to support cancer prevention.

Globally, cancer is a leading cause of death and morbidity and its burden is increasing worldwide. It is established that medical approaches alone will not solve this cancer crisis. Moreover, while cancer treatment can be effective, it is costly and access to treatment and health care is vastly inequitable. However, almost 50% of cancers are caused by potentially avoidable risk factors and are thus preventable. Cancer prevention represents the most cost-effective, feasible and sustainable pathway towards global cancer control. While much is known about cancer risk factors, prevention programs often lack consideration of how place impacts cancer risk over time. Maximizing cancer prevention investment requires an understanding of the geographic context for why some people develop cancer while others do not. Data on how community and individual level risk factors interact is therefore required. The Nova Scotia Community Cancer Matrix (NS-Matrix) study was established in Nova Scotia (NS), a small province in Eastern Canada with a population of 1 million. The study integrates small-area profiles of cancer incidence with cancer risk factors and socioeconomic conditions, to inform locally relevant and equitable cancer prevention strategies. The NS-Matrix Study includes over 99,000 incident cancers diagnosed in NS between 2001 and 2017, georeferenced to small-area communities. In this analysis we used Bayesian inference to identify communities with high and low risk for lung and bladder cancer: two highly preventable cancers with rates in NS exceeding the Canadian average, and for which key risk factors are high. We report significant spatial heterogeneity in lung and bladder cancer risk. The identification of spatial disparities relating to a community's socioeconomic profile and other spatially varying factors, such as environmental exposures, can inform prevention. Adopting Bayesian spatial analysis methods and utilizing high quality cancer registry data provides a model to support geographically-focused cancer prevention efforts, tailored to local community needs.

Capturing spatial dependence of COVID-19 case counts with cellphone mobility data.

Spatial dependence is usually introduced into spatial models using some measure of physical proximity. When analysing COVID-19 case counts, this makes sense as regions that are close together are more likely to have more people moving between them, spreading the disease. However, using the actual number of trips between each region may explain COVID-19 case counts better than physical proximity. In this paper, we investigate the efficacy of using telecommunications-derived mobility data to induce spatial dependence in spatial models applied to two Spanish communities' COVID-19 case counts. We do this by extending Besag York Mollié (BYM) models to include both a physical adjacency effect, alongside a mobility effect. The mobility effect is given a Gaussian Markov random field prior, with the number of trips between regions as edge weights. We leverage modern parametrizations of BYM models to conclude that the number of people moving between regions better explains variation in COVID-19 case counts than physical proximity data. We suggest that this data should be used in conjunction with physical proximity data when developing spatial models for COVID-19 case counts.

Mortality Associated with Ambient PM2.5 Exposure in India: Results from the Million Death Study.

BACKGROUND: Studies on the extent to which long-term exposure to ambient particulate matter (PM) with aerodynamic diameter ≤2.5µm (PM2.5) contributes to adult mortality in India are few, despite over 99% of Indians being exposed to levels that the World Health Organization (WHO) considers unsafe. OBJECTIVE: We conducted a retrospective cohort study within the Million Death Study (MDS) to provide the first-ever quantification of national mortality from exposure to PM2.5 in India from 1999 to 2014. METHODS: We calculated relative risks (RRs) by linking a total of ten 3-y intervals of satellite-based estimated PM2.5 exposure to deaths 3 to 5 y later in over 7,400 small villages or urban blocks covering a total population of 6.8 million. We applied using a model-based geostatistical model, adjusted for individual age, sex, and year of death; smoking prevalence, rural/urban residency, area-level female illiteracy, languages, and spatial clustering and unit-level variation. RESULTS: PM2.5 exposure levels increased from 1999 to 2014, particularly in central and eastern India. Among 212,573 deaths at ages 15-69 y, after spatial adjustment, we found a significant RR of 1.09 [95% credible interval (CI): 1.04, 1.14] for stroke deaths per 10-µg/m3 increase in PM2.5 exposure, but no significant excess for deaths from chronic respiratory disease and ischemic heart disease (IHD), all nonaccidental causes, and total mortality (after excluding stroke). Spatial adjustment attenuated the RRs for chronic respiratory disease and IHD but raised those for stroke. The RRs were consistent in various sensitivity analyses with spatial adjustment, including stratifying by levels of solid fuel exposure, by sex, and by age group, addition of climatic variables, and in supplementary case-control analyses using injury deaths as controls. DISCUSSION: Direct epidemiological measurements, despite inherent limitations, yielded associations between mortality and long-term PM2.5 inconsistent with those reported in earlier models used by the WHO to derive estimates of PM2.5 mortality in India. The modest RRs in our study are consistent with near or null mortality effects. They suggest suitable caution in estimating deaths from PM2.5 exposure based on MDS results and even more caution in extrapolating model-based associations of risk derived mostly from high-income countries to India. https://doi.org/10.1289/EHP9538.

Spatial patterns reveal negative density dependence and habitat associations in tropical trees.

Understanding how plant species coexist in tropical rainforests is one of the biggest challenges in community ecology. One prominent hypothesis suggests that rare species are at an advantage because trees have lower survival in areas of high conspecific density due to increased attack by natural enemies, a process known as negative density dependence (NDD). A consensus is emerging that NDD is important for plant-species coexistence in tropical forests. Most evidence comes from short-term studies, but testing the prediction that NDD decreases the spatial aggregation of tree populations provides a long-term perspective. While spatial distributions have provided only weak evidence for NDD so far, the opposing effects of environmental heterogeneity might have confounded previous analyses. Here we use a novel statistical technique to control for environmental heterogeneity while testing whether spatial aggregation decreases with tree size in four tropical forests. We provide evidence for NDD in 22% of the 139 tree species analyzed and show that environmental heterogeneity can obscure the spatial signal of NDD. Environmental heterogeneity contributed to aggregation in 84% of species. We conclude that both biotic interactions and environmental heterogeneity play crucial roles in shaping tree dynamics in tropical forests.

Population-weighted exposure to air pollution and COVID-19 incidence in Germany.

Many countries have enforced social distancing to stop the spread of COVID-19. Within countries, although the measures taken by governments are similar, the incidence rate varies among areas (e.g., counties, cities). One potential explanation is that people in some areas are more vulnerable to the coronavirus disease because of their worsened health conditions caused by long-term exposure to poor air quality. In this study, we investigate whether long-term exposure to air pollution increases the risk of COVID-19 infection in Germany. The results show that nitrogen dioxide (NO 2 ) is significantly associated with COVID-19 incidence, with a 1 µ g  m - 3 increase in long-term exposure to NO 2 increasing the COVID-19 incidence rate by 5.58% (95% credible interval [CI]: 3.35%, 7.86%). This result is consistent across various models. The analyses can be reproduced and updated routinely using public data sources and shared R code.

Long-term exposure to air pollution and COVID-19 incidence: A multi-country study.

The study of the impacts of air pollution on COVID-19 has gained increasing attention. However, most of the existing studies are based on a single country, with a high degree of variation in the results reported in different papers. We attempt to inform the debate about the long-term effects of air pollution on COVID-19 by conducting a multi-country analysis using a spatial ecological design, including Canada, Italy, England and the United States. The model allows the residual spatial autocorrelation after accounting for covariates. It is concluded that the effects of PM2.5 and NO2 are inconsistent across countries. Specifically, NO2 was not found to be an important factor affecting COVID-19 infection, while a large effect for PM2.5 in the US is not found in the other three countries. The Population Attributable Fraction for COVID-19 incidence ranges from 3.4% in Canada to 45.9% in Italy, although with considerable uncertainty in these estimates.

Bilateral Repetitive Transcranial Magnetic Stimulation Decreases Suicidal Ideation in Depression.

OBJECTIVE: The purpose of this study was to evaluate the effects of repetitive transcranial magnetic stimulation (rTMS) on suicidal ideation in patients with treatment-resistant major depression (TRD) (patients who failed to clinically respond to at least 2 medication trials). METHODS: We pooled data from 2 published prospective randomized controlled trials of rTMS applied to the dorsolateral prefrontal cortex in patients with TRD. We compared the effect of bilateral, left unilateral, and sham rTMS on suicidal ideation as measured by the suicide item of the 17-item Hamilton Depression Rating Scale (HDRS) (N = 156). RESULTS: Suicidal ideation resolved in 40.4%, 26.8%, and 18.8% of participants randomized to bilateral, left unilateral, and sham rTMS, respectively. The difference between bilateral and sham was significant (OR = 3.03; 95% CI, 1.19-7.71; P = .02), unlike the difference between left unilateral and sham (OR = 1.59; 95% CI, 0.61-4.12; P = .33). There was a modest correlation between change in suicidal ideation and change in depression severity (Pearson r = 0.38; P < .001) and no difference in change of HDRS-16 score between suicide remitters and nonremitters (P = .32). CONCLUSIONS: Bilateral rTMS was superior to sham rTMS in reducing suicidal ideation in patients with TRD. Only a small portion of the reduction in suicidal ideation was attributable to the reduction in depressive symptoms. These data suggest that suicidal ideation could be a specific target symptom construct for rTMS. TRIAL REGISTRATION: ClinicalTrials.gov identifiers: NCT01515215 and NCT00305045.