Assessing discrepancies in estimates of road traffic deaths in Brazil.

INTRODUCTION: The First UN Decade of Action for Road Safety (2011-2020) ended with most low/middle-income countries (LMICs) failing to reduce road traffic deaths. In contrast, Brazil reported a strong decline starting in 2012. However, comparisons with global health statistical estimates suggest that official statistics from Brazil under-report traffic deaths and overestimate declines. Therefore, we sought to assess the quality of official reporting in Brazil and explain discrepancies. METHODS: We obtained national death registration data and classified deaths to road traffic deaths and partially specified causes that could include traffic deaths. We adjusted data for completeness and reattributed partially specified causes proportionately over specified causes. We compared our estimates with reported statistics and estimates from the Global Burden of Disease (GBD)-2019 study and other sources. RESULTS: We estimate that road traffic deaths in 2019 exceeded the official figure by 31%, similar to traffic insurance claims (27.5%) but less than GBD-2019 estimates (46%). We estimate that traffic deaths have declined by 25% since 2012, close to the decline estimated by official statistics (27%) but much more than estimated by GBD-2019 (10%). We show that GBD-2019 underestimates the extent of recent improvements because GBD models do not track the trends evident in the underlying data. CONCLUSION: Brazil has made remarkable progress in reducing road traffic deaths in the last decade. A high-level evaluation of what has worked in Brazil could provide important guidance to other LMICs.

Identification and characterisation of SARS-CoV-2 and Human alphaherpesvirus 1 from a productive coinfection in a fatal COVID-19 case.

BACKGROUND: During routine Coronavirus disease 2019 (COVID-19) diagnosis, an unusually high viral load was detected by reverse transcription real-time polymerase chain reaction (RT-qPCR) in a nasopharyngeal swab sample collected from a patient with respiratory and neurological symptoms who rapidly succumbed to the disease. Therefore we sought to characterise the infection. OBJECTIVES: We aimed to determine and characterise the etiological agent responsible for the poor outcome. METHODS: Classical virological methods, such as plaque assay and plaque reduction neutralisation test combined with amplicon-based sequencing, as well as a viral metagenomic approach, were performed to characterise the etiological agents of the infection. FINDINGS: Plaque assay revealed two distinct plaque phenotypes, suggesting either the presence of two severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) strains or a productive coinfection of two different species of virus. Amplicon-based sequencing did not support the presence of any SARS-CoV-2 genetic variants that would explain the high viral load and suggested the presence of a single SARS-CoV-2 strain. Nonetheless, the viral metagenomic analysis revealed that Coronaviridae and Herpesviridae were the predominant virus families within the sample. This finding was confirmed by a plaque reduction neutralisation test and PCR. MAIN CONCLUSIONS: We characterised a productive coinfection of SARS-CoV-2 and Herpes simplex virus 1 (HSV-1) in a patient with severe symptoms that succumbed to the disease. Although we cannot establish the causal relationship between the coinfection and the severity of the clinical case, this work serves as a warning for future studies focused on the interplay between SARS-CoV-2 and HSV-1 coinfection and COVID-19 severity.

Identification and characterisation of SARS-CoV-2 and Human alphaherpesvirus 1 from a productive coinfection in a fatal COVID-19 case

BACKGROUND During routine Coronavirus disease 2019 (COVID-19) diagnosis, an unusually high viral load was detected by reverse transcription real-time polymerase chain reaction (RT-qPCR) in a nasopharyngeal swab sample collected from a patient with respiratory and neurological symptoms who rapidly succumbed to the disease. Therefore we sought to characterise the infection. OBJECTIVES We aimed to determine and characterise the etiological agent responsible for the poor outcome. METHODS Classical virological methods, such as plaque assay and plaque reduction neutralisation test combined with amplicon-based sequencing, as well as a viral metagenomic approach, were performed to characterise the etiological agents of the infection. FINDINGS Plaque assay revealed two distinct plaque phenotypes, suggesting either the presence of two severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) strains or a productive coinfection of two different species of virus. Amplicon-based sequencing did not support the presence of any SARS-CoV-2 genetic variants that would explain the high viral load and suggested the presence of a single SARS-CoV-2 strain. Nonetheless, the viral metagenomic analysis revealed that Coronaviridae and Herpesviridae were the predominant virus families within the sample. This finding was confirmed by a plaque reduction neutralisation test and PCR. MAIN CONCLUSIONS We characterised a productive coinfection of SARS-CoV-2 and Herpes simplex virus 1 (HSV-1) in a patient with severe symptoms that succumbed to the disease. Although we cannot establish the causal relationship between the coinfection and the severity of the clinical case, this work serves as a warning for future studies focused on the interplay between SARS-CoV-2 and HSV-1 coinfection and COVID-19 severity.

Internationally comparable diagnosis-specific survival probabilities for calculation of the ICD-10-based Injury Severity Score.

BACKGROUND: The International Statistical Classification of Diseases, 10th Revision (ICD-10)-based Injury Severity Score (ICISS) performs well but requires diagnosis-specific survival probabilities (DSPs), which are empirically derived, for its calculation. The objective was to examine if DSPs based on data pooled from several countries could increase accuracy, precision, utility, and international comparability of DSPs and ICISS. METHODS: Australia, Argentina, Austria, Canada, Denmark, New Zealand, and Sweden provided ICD-10-coded injury hospital discharge data, including in-hospital mortality status. Data from the seven countries were pooled using four different methods to create an international collaborative effort ICISS (ICE-ICISS). The ability of the ICISS to predict mortality using the country-specific DSPs and the pooled DSPs was estimated and compared. RESULTS: The pooled DSPs were based on a total of 3,966,550 observations of injury diagnoses from the seven countries. The proportion of injury diagnoses having at least 100 discharges to calculate the DSP varied from 12% to 48% in the country-specific data set and was 66% in the pooled data set. When compared with using a country's own DSPs for ICISS calculation, the pooled DSPs resulted in somewhat reduced discrimination in predicting mortality (difference in c statistic varied from 0.006 to 0.04). Calibration was generally good when the predicted mortality risk was less than 20%. When Danish and Swedish data were used, ICISS was combined with age and sex in a logistic regression model to predict in-hospital mortality. Including age and sex improved both discrimination and calibration substantially, and the differences from using country-specific or pooled DSPs were minor. CONCLUSION: Pooling data from seven countries generated empirically derived DSPs. These pooled DSPs facilitate international comparisons and enables the use of ICISS in all settings where ICD-10 hospital discharge diagnoses are available. The modest reduction in performance of the ICE-ICISS compared with the country-specific scores is unlikely to outweigh the benefit of internationally comparable Injury Severity Scores possible with pooled data. LEVEL OF EVIDENCE: Prognostic and epidemiological study, level III.