Epidemiological Variables Research Articles

Dinâmica temporal de Plasmopara viticola em função do aumento da carga de gemas em 'Sauvignon Blanc'

Abstract The objective of this work was to evaluate the effect of increasing bud load per plant on epidemiological variables of downy mildew on 'Sauvignon Blanc'. The study was carried out in a commercial vineyard in a high-altitude region of the municipality of São Joaquim, in the state of Santa Catarina, Brazil, during the 2016/2017 and 2017/2018 vintages. The treatments consisted of four bud loads: 15, 30, 50, and 75 per vine. The maximum incidence, maximum severity, beginning of symptom appearance, time to reach maximum disease incidence and severity, area under the incidence and severity disease progress curve were determined. Increasing bud load over 50 per vine results in higher incidence and severity of downy mildew (Plasmopara viticola) in 'Sauvignon Blanc' leaves but does not influence the time to reach maximum disease incidence and severity. Increasing bud load over 50 per vine results in an increase in the area under the disease incidence and severity progress curve for downy mildew in 'Sauvignon Blanc' leaves. To adopt over 50 buds per vine treatment, it is necessary additional disease control measures, with an emphasis on integrated management to control downy mildew.

The prevalence of tuberculosis infection in India: A systematic review and meta-analysis.

The National Prevalence Survey of India (2019-2021) estimated 31 per cent tuberculosis infection (TBI) burden among individuals above 15 years of age. However, so far little is known about the TBI burden among the different risk groups in India. Thus, this systematic review and meta-analysis, aimed to estimate the prevalence of TBI in India based on geographies, sociodemographic profile, and risk groups. To identify the prevalence of TBI in India, data sources such as MEDLINE, EMBASE, CINAHL, and Scopus were searched for articles reporting data between 2013-2022, irrespective of the language and study setting. TBI data were extracted from 77 publications and pooled prevalence was estimated from the 15 community-based cohort studies. Articles were reviewed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines and were sourced using a predefined search strategy from different databases. Out of 10,521 records, 77 studies (46 cross-sectional and 31 cohort studies) were included. The pooled TBI prevalence for India based on the community-based cohort studies was estimated as 41 per cent [95% confidence interval (CI) 29.5-52.6%] irrespective of the risk of acquiring it, while the estimation was 36 per cent (95% CI 28-45%) prevalence observed among the general population excluding high-risk groups. Regions with high active TB burden were found to have a high TBI prevalence such as Delhi and Tamil Nadu. An increasing trend of TBI was observed with increasing age in India. This review demonstrated a high prevalence of TBI in India. The burden of TBI was commensurate with active TB prevalence suggesting possible conversion of TBI to active TB. A high burden was recorded among people residing in the northern and southern regions of the country. Such local epidemiologic variation need to be considered to reprioritize and implement-tailored strategies for managing TBI in India.

EVIDENCE-BASED OCCUPATIONAL RISK OF CORONAVIRUS DISEASE (COVID-19) AMONG HEALTH WORKERS

Introduction: Epidemiologic variables (prevalence and impact) of coronavirus disease were evaluated among health workers to elucidate the occupational risk of frontline fighters of the viral infection. 
 Methods: This is a descriptive study performed from September to December 2021 on all consenting healthcare workers (HCWs) in a health facility in southern Nigeria. Data collected were statistically analyzed using SPSS version 23.
 Results: About 339 volunteered HWs consisting of doctors 88 (26.0%), nurses 78 (23.0%), midwives 54 (15.9%), laboratory scientists 32 (9.4%), pharmacists 21 (6.2%), Public Health Surveillance Officer 29 (8.6%), psychosocial counselor 11 (3.2%), administrative officers 17 (5.0%) and others 9 (2.7%) were involved in the study. About 98 (28.9%) were COVID-19 patients while 241 (71.1%) were healthy. Among 98 unhealthy HCWs, 55 (56.1%) were male, and 43 (43.9%) with an age range of 18 – 79 years. The symptoms distribution produced among the unhealthy volunteers included; fever 12 (12.2%), dry cough 17 (17.3%), productive cough 6 (6.1%), Dyspnea 7 (7.1%), Anosmia 9 (9.2%), headache 8 (8.2%), fatigue 8 (8.2%), Myalgia 4 (4.1%), Aguesia 6(6.1%), Diarrhea 4 (4.1%), sore throat 5 (5.1%), Rhinorrhea 3 (3.1%), Vomiting 2 (2.0%) and Others 7 (7.1%). The study also showed that there was a significant distribution of anxiety and depression among the frontline fighters, P<0.05.
 Conclusion: The distribution and impact of the virus observed among clinical and clinical support staff in this study provided an evidence-based occupational risk of the virus on HCWs, especially the frontline fighters; Hence, forming a basis for the need to put in place measures to manage and curtail the viral infection rate in hospital facilities in addition to enhancing prevention behavior of HCWs.

An extended Susceptible-Exposed-Infected-Recovered (SEIR) model with vaccination for forecasting the COVID-19 pandemic in Sri Lanka

Background: After declaration of a Public Health Emergency of International Concern (PHEIC) by the World Health Organization, Novel Corona Virus had been spreading throughout the world despite various degrees of movement restrictions and availability of multiple safe and effective vaccines. Vaccination rate against COVID-19 is one of the infection rate’s main determinants. The role of modelling in predicting the spread of an epidemic is important for health planning and policy making.Objective: This study aimed to construct a compartmental epidemiological model incorporating vaccination coverage, vaccination rate, vaccine efficacies and applied a computational tool for predicting the evolution of different epidemiological variables for COVID-19 in Sri Lanka.Methods: We used a dynamic Susceptible-Exposed-Infected-Recovered-Vaccinated (SEIRV) model and simulated potential vaccine strategies under a range of epidemic conditions. The predictions were based on different vaccination coverages (5% to 90%), vaccination-rates (1%, 2%, 5%) and vaccine-efficacies (40%, 60%, 80%) under different R0 (2,4,6). We estimated the duration, exposed, and infected populations.Results: When the R0 was increased, the days of reduction of susceptibility and the days to reach the peak of the infection were reduced gradually. At least 45% vaccine coverage is required for reducing the infected COVID-19 population to mitigate a disastrous situation in Sri Lanka.Conclusion and recommendations: The results revealed that when R0 is increased in the SEIRV model along with the increase of vaccination efficacy and vaccination rate, the population to be vaccinated is reducing. Thus, the vaccination offers greater benefits to the local population by reducing the time to reach the peak, exposed and infected population through flattening the curves. The prediction models will lead to policy relevance despite the significant uncertainty associated with real-time forecasting in complex systems with timely predictions and steadfast reports.

App-ExploraCítricos, a digital development for integrate pest surveillance in citrus crops

App-ExploraCitricos v2.0 is an application for assessing epidemiological variables with a spatio-temporal, multicrop, multivariety-species, multivariable, multi-pest, multi-user and multi-criteria approach for risk analysis in the citrus productive chain. This work aimed to develop an application for Android® mobile devices higher than 5.0, allowing in situ evaluations associated with epidemiological or phytosanitary processes through a flexible design customized to the user's criteria. The process is initiated by logging into the application with passwords, previously registered, for authentication. Before an assessment, users are required to register only once n-pests and/or n-diseases associated with the citrus crop(s)/species concerned, providing the common and scientific name, and organism type (fungus, virus, bacterium, etc.). Entries are stored locally available for future assessments. Later, set up assessment n-scales with n-classes to quantify damage/severity. Versatility allows entry of qualitative (e.g. healthy, sick, dead) or quantitative scales (e.g. 0, <25%, 25-50% and >50%). It also enables to assess presence/absence and quantify vector if required. By customizing the assessment, choose the pest(s) concerned and associated scale. At the moment of evaluation, a plantation is parameterized by 26 epidemiological-productive variables, e.g., agronomic condition, age, crop, variety/cultivar, irrigation type, nutrition, management, etc. Assessment is performed for n-plants defined by the user. Per plant, the selected pathogen-pest(s) and scale class is assessed. Optionally, up to three geo-referenced photographs of symptoms or other aspect of concern can be taken. At the end, assessment(s) are sent to a database web platform. Assessments per planting are exported in MS-Excel for sharing via email, bluetooth, social networks or other device tools.

Lower Urinary Tract Diseases in Guinea Pigs: A 14-Year Retrospective Study (2004-2018).

The clinical records of all guinea pigs diagnosed with a lower urinary tract disease in a single veterinary hospital, over a period of 14 years (2004−2018), were retrospectively searched in order to characterize this population and investigate the potential association between the epidemiological and clinical variables. A total of 117 clinical cases were identified, corresponding to 57 animals. Urolithiasis was the most common diagnosis (n = 52; 44.4%), followed by cystitis and/or a urinary tract infection (UTI). Several statistically significant associations (p < 0.05) were found between different variables, showing that female guinea pigs were more likely than the male ones to have a previous family history of urinary disease, to present dysuria and stranguria at admission, and to suffer recurrence. Moreover, males were more prone to urolithiasis and females to cystitis/UTI, and animals diagnosed with cystitis/UTI frequently had more clinical urinary signs and abdominal pain on palpation compared to those diagnosed with urolithiasis. Finally, the use of potassium citrate and the urethrotomy approach were associated with a better therapeutic response. Further studies are needed in larger populations of guinea pigs to confirm the present findings, especially as some of them were described for the first time.

International monitoring of capacity of treatment systems for alcohol and drug use disorders: Methodology of the Service Capacity Index for Substance Use Disorders.

We aimed to develop a Service Capacity Index for Substance Use Disorders (SCI-SUD) that would reflect the capacity of national health systems to provide treatment for alcohol and drug use disorders, in terms of the proportion of available service elements in a given country from a theoretical maximum. Data were collected through the WHO Global Survey on Progress with Sustainable Development Goals (SDG) Health Target 3.5, conducted between December 2019 and July 2020 to produce the SCI-SUD, based on 378 variables overall. The SCI-SUD was directly derived for 145 countries. We used multiple imputation to produce comparable SCI-SUD estimates for countries that did not submit data (40 countries) or had very high level of missingness (9 countries). The final SCI-SUD demonstrates considerable consistency and internal stability and is strongly associated with the macro-level economic, healthcare-related and epidemiologic (such as prevalence rates) variables. The presented methodology represents a step forward in monitoring the global situation in regard to the development of treatment systems for SU disorders, however, further work is warranted to improve the external validity of the measure (e.g., in-depth data generation in countries) and ensure its feasibility for regular reporting (e.g., reducing the number of variables).

Prediction of new onset atrial fibrillation recurrence or persistence with artificial intelligence: first insights of the PRAFAI study

Abstract Introduction Atrial fibrillation (AF) is the most prevalent arrhythmia in the world and it is associated with a high rate of cardiovascular morbidity and mortality. A higher burden of atrial fibrillation is related to more adverse cardiovascular events and the rhythm control strategy (maintenance or recovery of sinus rhythm) is particularly indicated in patients with paroxysmal symptomatic atrial fibrillation. All things considered, in order to select the optimal therapeutic strategy, it might be useful to accurately predict the probability of recurrence or permanence of AF after its onset. The predictive models implemented so far, show a limited predictive power or were built on samples of patients undergoing specific therapies. Thus, developing an specific model based on features derived from electronic health records (EHR) of patients with a first AF episode seems essential. Purpose To develop an artificial intelligence powered predictive model based on EHR variables in order to predict the AF recurrence after its onset. Methods The methodological design of the research is based on the analysis of secondary data from a retrospective cohort obtained from the EHR of a tertiary hospital. All new onset AF from 2015 to 2018 were identified by ICD codes, and a 2 years EHR driven follow-up was made to determine the AF recurrence or permanence of the arrhythmia in those patients. A systematic review was pursued to determine which features exhibited a greater predictive power for AF recurrence, and they were inquired to the system for the mentioned participants. After the standardization of the variables and a feature selection process, several missing value imputation methods and around 12 different Machine Learning algorithms were tested to predict the AF recurrence in a subset of patients who developed AF in the first semester of 2015, in order to select the algorithms with the highest prediction accuracy for further tests. Results 523 patients had an AF onset in the first semester of 2015. Among them, 310 (59.3%) had AF recurrence in a 2 years period. A support vector machine (SVM) algorithm with a median imputation method to handle missing values performed the best and had an 0.77 AUC in the training set and 0.71 in the test set. Hyperthyroidism, vasodilator drug use and obstructive sleep apnea were notoriously related to AF recurrence, while Ic antiarrhythmic drugs, AF ablation, cognitive impairment and anxiety were the most influential variables for the absence of recurrence. Classical AF recurrence factors such as age or left atrium diameter ratify their role in this setting. Conclusion A SVM Machine Learning algorithm discloses an accurate AF recurrence probability based on EHR features. Pharmacologic and epidemiological variables, added to classically assessed ones, seem to be specially related to this arrhythmic recurrence. Further research including the whole cohort features will probably improve the accuracy of this selected SVM algorithm. Funding Acknowledgement Type of funding sources: None.

Seroprevalence of Toxocariasis Among Hypereosinophilic Children: A Single Center Study, Tehran, Iran

Background: Toxocariasis is a parasitic disease causing hypereosinophilia. This study aimed to investigate the serological prevalence of toxocariasis among hypereosinophilic children in Children’s Medical Center, Tehran, Iran, as well as to explore its relationship with epidemiological variables and some blood indices. Methods: This descriptive cross-sectional study was performed in 2020 on children referred to referral children hospital for routine tests. A total of 282 children diagnosed with hypereosinophilia were selected and included in the study, and then, their serum was collected. After obtaining informed consent from their parents, the parents were asked to fill out a questionnaire. The serological ELISA test was used to assess the anti-Toxocara IgG antibody. Data were analyzed using SPSS software 18. Results: Out of 282 hypereosinophilic children, 17 (6%) had serological results positive for anti-Toxocara antibody. The mean age of children with toxocariasis was higher than that of children without toxocariasis (P = 0.312). Furthermore, ESR and CRP variables were significantly higher in infected children than those in non-infected children (P &lt; 0.05). Conclusions: The results of the present study confirmed the relationship between toxocariasis and hypereosinophilia. Since the symptoms of toxocariasis are non-specific and may go undiagnosed, it was found necessary to examine toxocariasis in cases of hypereosinophilic individuals.

Comprehensive Genome Analysis of Neisseria meningitidis from South America Reveals a Distinctive Pathogenicity-Related Prophage Repertoire

Neisseria meningitidis, a bacterium that colonizes in the human nasopharynx, occasionally causes invasive meningococcal disease leading to meningitis or septicemia. Different serogroups and lineages (clonal complexes) are related to the occurrence and epidemiology of N. meningitidis. Despite vaccines for most serogroups, N. meningitidis lineages causing unusual clinical manifestations and a higher fatality rate compared to other lineages have been reported in South America. The present study focused on exploring the diversity of N. meningitidis prophages from South America and their relationship with the epidemiological variables of these strains. We found a high diversity of prophages among the different clonal complexes. By comparing them with previously described N. meningitidis phages and prophages, we revealed groups of prophages sharing similar compositions, which could be useful for prophage comparison in N. meningitidis. Furthermore, we observed a high correlation between the prophage content and epidemiological features, e.g., pathogenicity or clonal complex. Additionally, a distinctive filamentous prophage named here as IMSAR-11 (Invasive Meningococci from South America Related to cc11) was identified. Interestingly, two versions of IMSAR-11, circular and chromosomally integrated, were found. Overall, this study reinforces the importance of the genomic characterization of circulating N. meningitidis lineages to generate new targets for lineage monitoring, diagnosis, or appropriateness of vaccine development. Further studies are necessary to understand the role of these prophages in the persistence, dispersal, and virulence of N. meningitidis in the world.

Correlation between Blunted Nocturnal Decrease in Diastolic Blood Pressure and Oxidative Stress: An Observational Study.

An impaired nocturnal decrease in diastolic blood pressure (DBP) increases the blood pressure (BP) load, which is a main factor in endothelial dysfunction, atherosclerosis, and arterial stiffness. We aimed to quantify some markers of oxidative stress in hypertensive patients, to compare their levels between individuals with dipper and non-dipper DBP profiles, and to assess their correlation with the nocturnal DBP (nDBP) dipping. It was an observational study that included patients older than 18 years with a diagnosis of essential hypertension who consented to participate. The collected variables were some indices of 24-h ambulatory blood pressure monitoring, demographic, epidemiological, clinical, and laboratory variables. Plasma thiobarbituric acid reactive substances (TBARS) and reduced thiols, together with serum vitamin E, vitamin A, copper (Cu), and zinc (Zn) levels were assessed as oxidative stress markers. We recruited 248 patients with a median age of 56 years (56% women). The percentage of nDBP dipping showed a weak positive correlation with reduced thiol, vitamin E, and vitamin A levels; and a weak negative correlation with Cu levels. We also found a negative correlation between nDBP dipping and the TBARS/Thiol, TBARS/Vitamin E, and TBARS/Vitamin A ratios. After multivariate analysis, we found that increased TBARS/Thiol ratio and serum Cu levels were associated with a higher risk of a non-dipper DBP profile. As in other situations of increased cardiovascular risk, an impaired nDBP decrease may coincide with abnormalities in redox status.

Linking integrative taxonomy and ecology: Diversity and population structure of two platyhelminth parasites (Digenea: Lepidapedidae) of sympatric deep-sea fishes in the Western Mediterranean

Current knowledge about deep-sea parasites is limited and the data shedding light on population differentiation at host, geographical or bathymetric scales are scarce. Here, we applied an integrative taxonomic approach to the identification of metazoan parasites in a large sample of deep-sea fish species from the Western Mediterranean and assessed the diversity of Lepidapedon spp. (Digenea) and the patterns of genetic and epidemiological variation of parasite populations in relation to host, geographical and bathymetric provenance. Fully censused infrapopulations of Lepidapedon spp. were analysed from five species of deep-sea fish (Coelorinchus mediterraneus (Mediterranean grenadier), Lepidion lepidion (Mediterranean codling), Phycis blennoides (greater forkbeard), Trachyrincus scabrus (roughsnout grenadier) and Mora moro (common mora)) collected by bottom trawling at depths of 400–2000 m. Partial fragments of the mitochondrial nad1 gene amplified for representative samples per morphotype were used to aid species delineation. After completion of the combined morphological and molecular characterisation of select samples, the total collected material was re-identified based on a suite of differentiating morphological features. Analyses revealed low species diversity and host specificity of Lepidapedon spp. Two species infecting multiple hosts were identified: Lepidapedon desclersae and L. guevarai. Genetic analyses showed lack of genetic differentiation for populations of the more abundantly sequenced species, whereas ecological analyses depicted significant differences in epidemiological parameters of both digenean species associated with host species, geographical area and bathymetric range. Overall, our results indicate that combining population genetics with ecological analyses holds a promise of gaining insights into the factors and possible mechanisms that determine the patterns of connectivity among parasite populations in the deep sea.

Likely Electromagnetic Foundations of Gender Inequality

Cross-country variation of gender inequality is attributed to cultural, evolutionary, epidemiological, social, and psychological variables, but recent research has shown decreased inequality with proximity to the poles, suggesting that such variables may convey effects of electromagnetics and climate. This study evaluated two mediation models across 98 countries. In the successful model, ultraviolet radiation impaired cognitive performance with the final result of increasing gender inequality; cross-cultural research should pay attention to this three-part connection and specify the process in greater detail. Additionally, gender inequality emerged directly related to ultraviolet radiation with positive sign, suggesting actions of testosterone; field and laboratory studies that address the specific mediating roles of sex hormones are needed. Pathogen prevalence and the ACP1*B allele played complementary roles that are consistent with the literature. The model was robust to post-1500 European ancestry and the radiation – cognitive performance – gender inequality nexus, but not other paths, were reliable across continents.

Testing a simple and frugal model of health protective behaviour in epidemic times

The COVID-19 epidemic highlighted the necessity to integrate dynamic human behaviour change into infectious disease transmission models. The adoption of health protective behaviour, such as handwashing or staying at home, depends on both epidemiological and personal variables. However, only a few models have been proposed in the recent literature to account for behavioural change in response to the health threat over time. This study aims to estimate the relevance of TELL ME, a simple and frugal agent-based model developed following the 2009 H1N1 outbreak to explain individual engagement in health protective behaviours in epidemic times and how communication can influence this. Basically, TELL ME includes a behavioural rule to simulate individual decisions to adopt health protective behaviours. To test this rule, we used behavioural data from a series of 12 cross-sectional surveys in France over a 6-month period (May to November 2020). Samples were representative of the French population (N = 24,003). We found the TELL ME behavioural rule to be associated with a moderate to high error rate in representing the adoption of behaviours, indicating that parameter values are not constant over time and that other key variables influence individual decisions. These results highlight the crucial need for longitudinal behavioural data to better calibrate epidemiological models accounting for public responses to infectious disease threats.

Malaria in the eco-epidemiological region of the Colombian Caribbean, 1960-2019.

Motivation for the study: the information available on the epidemiology of malaria in the Colombian Caribbean region is incomplete, poorly systematized and its dissemination is limited. This has led to a lack of knowledge of its magnitude and a low perception of its importance as a public health problem. Main findings: the behavior of malaria is endemic-epidemic, with low to very low transmission, focused and with irregular outbreaks. Plasmodium vivax infections predominate. Implications: the results of this study contribute to improve evidence-based decision making for the implementation of malaria eradication plans. Malaria has a heterogeneous and variable behavior among Colombian regions. In order to establish its epidemiological behavior in the Colombian Caribbean region between 1960 and 2019, we carried out an observational, descriptive and retrospective study based on records from the Ministry of Health and other secondary sources. We defined epidemiological variables and used measures of frequency and central tendency. A total of 155,096 cases were registered. The decades with the highest number of cases were 1990-1999 (20.5%) and 1980-1989 (18.9%). The average number of cases per decade was 25,849.3. The highest parasite rates were recorded in 1970 (3.3 per 1000 population) and 1981 (3.9 per 1000 population). Plasmodium vivax was the most frequent species and most of the burden by age group was found in people under 29 years of age, between 2010-2019. Malaria showed an endemic-epidemic pattern of low and very low transmission intensity, with a decreasing trend.

COVID-19 in Europe: from outbreak to vaccination

BackgroundCOVID-19 is a pandemic of unprecedented proportions in recent human history. To date, the world has paid a high toll in terms of human lives lost, and on economic, financial, and social repercussions. In Europe, countries tried to mobilize all resources available to contain the COVID-19 effects, but the outcomes are diverse across countries. There have also been massive efforts geared towards finding safe and effective vaccines and to distribute them massively to the population. The main objective of this paper is to describe the COVID-19 prevalence in Europe. Secondly, it aims to identify epidemiological typologies allowing to distinguish the countries in terms of their response to the pandemic, and finally assess the effect of vaccination on pandemic control.MethodsThe study covers 30 European countries: EU 27 in addition to Norway, Switzerland, and United Kingdom. Four epidemiological variables are analyzed at two distinct moments, at the end of 2020 and at the beginning of 2022: total number of cases per million, total number of deaths per million, total number of tests per thousand, and case fatality rate. In a second step, it uses a fuzzy approach, namely archetypal analysis, to identify epidemiological typologies, and positions countries by their response to the pandemic. Finally, it assesses how vaccination, stringency measures, booster doses and population age affect the case fatality rate, using a multiple regression model.ResultsThe outcomes unveil four epidemiological typologies for both periods. The clearest sign of change in the two periods concerns the case fatality rate that is found to be low in a single typology in 2020 but occurs in three typologies in 2022, although to different degrees. There is also statistical evidence of the positive impact of the primary vaccination on mortality reduction; however, the same does not hold for the booster dose and stringency measures.ConclusionsThe study shows that primary vaccination is the most effective measure to reduce mortality by COVID-19 suggesting that vaccination provides hope for an end to the pandemic. However, a worldwide access to vaccination is needed to make this happen.

Tiered social distancing policies and epidemic control

Tiered social distancing policies have been adopted by many governments to mitigate the harmful consequences of COVID-19. Such policies have a number of well-established features, i.e. they are short-term, adaptive (to the changing epidemiological conditions), and based on a multiplicity of indicators of the prevailing epidemic activity. Here, we use ideas from Behavioural Epidemiology to represent tiered policies in an SEIRS model by using a composite information index including multiple indicators of current and past epidemic activity mimicking those used by governments during the COVID-19 pandemic, such as transmission intensity, infection incidence and hospitals’ occupancy. In its turn, the dynamics of the information index is assumed to endogenously inform the governmental social distancing interventions. The resulting model is described by a hereditary system showing a noteworthy property, i.e. a dependency of the endemic levels of epidemiological variables from initial conditions. This is a consequence of the need to normalize the different indicators to pool them into a single index. Simulations suggest a rich spectrum of possible results. These include policy suggestions and identify pitfalls and undesired outcomes, such as a worsening of epidemic control, that can arise following such types of approaches to epidemic responses.

Epidemiological Characteristics of Deaths from COVID-19 in Peru during the Initial Pandemic Response.

Peru is the country with the highest mortality rate from COVID-19 globally, so the analysis of the characteristics of deaths is of national and international interest. The aim was to determine the epidemiological characteristics of deaths from COVID-19 in Peru from 28 March to 21 May 2020. Deaths from various sources were investigated, including the COVID-19 Epidemiological Surveillance and the National System of Deaths (SINADEF). In all, 3851 deaths that met the definition of a confirmed case and had a positive result of RT-PCR or rapid test IgM/IgG, were considered for the analysis. We obtained the epidemiological variables and carried out an analysis of time defined as the pre-hospital time from the onset of symptoms to hospitalization, and hospital time from the date of hospitalization to death. Deaths were more frequent in males (72.0%), seniors (68.8%) and residents of the region of Lima (42.7%). In 17.8% of cases, the death occurred out-of-hospital, and 31.4% had some comorbidity. The median of pre-hospital time was 7 days (IQR: 4.0-9.0) and for the hospital time was 5 days (IQR: 3.0-9.0). The multivariable analysis with Poisson regression with robust variance found that the age group, comorbidity diagnosis and the region of origin significantly influenced pre-hospital time; while sex, comorbidity diagnosis, healthcare provider and the region of origin significantly influenced hospital time. Deaths occurred mainly in males, seniors and on the coast, with considerable out-of-hospital deaths. Pre-hospital time was affected by age group, the diagnosis of comorbidities and the region of origin; while, hospital time was influenced by gender, the diagnosis of comorbidities, healthcare provider and the region of origin.

Association Between Broadband Capacity and Social Vulnerability Factors in the United States: A County-Level Spatial Analysis.

This study evaluated relationships between county-level social vulnerability and broadband access using spatial clustering and regression approaches. County-level broadband availability (Federal Communications Commission [FCC] and Microsoft; 2019-2020), social vulnerability (COVID-19 Community Vulnerability Index [CCVI]; 2020), and primary care access (Area Health Resource File; 2019-2020) data sets were used. Two measures of broadband availability were considered: (1) Microsoft system-reported proportion of county population with broadband and (2) difference in FCC-reported and Microsoft-reported proportions of county population with broadband. Cluster maps were constructed using local Moran's I, and spatial Durbin models were estimated using primary care shortage designation and CCVI themes (socioeconomic status, minority status, housing/transportation/disability, epidemiological risk, health care system, high-risk environment, and population density). Among 3102 counties, county-level broadband coverage varied widely between Microsoft (0.39) and FCC (0.84), with greater coverage in the East and West, and larger discrepancies between FCC and Microsoft data in the South and Appalachia. In spatial regressions, a one-point increase in socioeconomic status vulnerability (0-least; 10-most vulnerable), was associated with a 2.0 percentage point (pp) reduction in broadband access (P < 0.001). Similar inverse relationships were observed with housing, epidemiological, and health care system variables. There were greater divergences between FCC and Microsoft measures with each one-point increase in socioeconomic status (1.4 pp), epidemiological risk (0.6 pp), and health care system (0.7 pp) vulnerability. More vulnerable counties had lower broadband and larger divergences between FCC and Microsoft data. Broadband is necessary for utilizing telehealth services; careful considerations in measuring broadband access can facilitate policies that improve equitable access to care.

Seroepidemiology of SARS-CoV-2 on a partially vaccinated island in Brazil: Determinants of infection and vaccine response.

A vaccination campaign targeted adults in response to the pandemic in the City of Rio de Janeiro. We aimed to evaluate the seroprevalence of SARS-CoV-2 antibodies and identify factors associated with seropositivity on vaccinated and unvaccinated residents. We performed a seroepidemiologic survey in all residents of Paquetá Island, a neighborhood of Rio de Janeiro city, during the COVID-19 vaccine roll-out. Serological tests were performed from June 16 to June 19, 2021, and adjusted seropositivity rates were estimated by age and epidemiological variables. Logistic regression models were used to estimate adjusted ORs for risk factors to SARS-CoV-2 seropositivity in non-vaccinated individuals, and potential determinants of the magnitude of antibody responses in the seropositive population. We included in the study 3,016 residents of Paquetá (83.5% of the island population). The crude seroprevalence of COVID-19 antibodies in our sample was 53.6% (95% CI = 51.0, 56.3). The risk factors for SARS-CoV-2 seropositivity in non-vaccinated individuals were history of confirmed previous COVID-19 infection (OR = 4.74; 95% CI = 3.3, 7.0), being a household contact of a case (OR = 1.93; 95% CI = 1.5, 2.6) and in-person learning (OR = 2.01; 95% CI = 1.4, 3.0). Potential determinants of the magnitude of antibody responses among the seropositive were hybrid immunity, the type of vaccine received, and time since the last vaccine dose. Being vaccinated with Pfizer or AstraZeneca (Beta = 2.2; 95% CI = 1.8, 2.6) determined higher antibody titers than those observed with CoronaVac (Beta = 1.2; 95% CI = 0.9, 1.5). Our study highlights the impact of vaccination on COVID-19 collective immunity even in a highly affected population, showing the difference in antibody titers achieved with different vaccines and how they wane with time, reinforcing how these factors should be considered when estimating effectiveness of a vaccination program at any given time. We also found that hybrid immunity was superior to both infection-induced and vaccine-induced immunity alone, and online learning protected students from COVID-19 exposure.