Alternative epidemic indicators for COVID-19 in three settings with incomplete death registration systems

Not all COVID-19 deaths are officially reported, and particularly in low-income and humanitarian settings, the magnitude of reporting gaps remains sparsely characterized. Alternative data sources, including burial site worker reports, satellite imagery of cemeteries, and social media-conducted surveys of infection may offer solutions. By merging these data with independently conducted, representative serological studies within a mathematical modeling framework, we aim to better understand the range of underreporting using examples from three major cities: Addis Ababa (Ethiopia), Aden (Yemen), and Khartoum (Sudan) during 2020. We estimate that 69 to 100%, 0.8 to 8.0%, and 3.0 to 6.0% of COVID-19 deaths were reported in each setting, respectively. In future epidemics, and in settings where vital registration systems are limited, using multiple alternative data sources could provide critically needed, improved estimates of epidemic impact. However, ultimately, these systems are needed to ensure that, in contrast to COVID-19, the impact of future pandemics or other drivers of mortality is reported and understood worldwide

Global injury morbidity and mortality from 1990 to 2017 : results from the Global Burden of Disease Study 2017

Correction:Background Past research in population health trends has shown that injuries form a substantial burden of population health loss. Regular updates to injury burden assessments are critical. We report Global Burden of Disease (GBD) 2017 Study estimates on morbidity and mortality for all injuries. Methods We reviewed results for injuries from the GBD 2017 study. GBD 2017 measured injury-specific mortality and years of life lost (YLLs) using the Cause of Death Ensemble model. To measure non-fatal injuries, GBD 2017 modelled injury-specific incidence and converted this to prevalence and years lived with disability (YLDs). YLLs and YLDs were summed to calculate disability-adjusted life years (DALYs). Findings In 1990, there were 4 260 493 (4 085 700 to 4 396 138) injury deaths, which increased to 4 484 722 (4 332 010 to 4 585 554) deaths in 2017, while age-standardised mortality decreased from 1079 (1073 to 1086) to 738 (730 to 745) per 100 000. In 1990, there were 354 064 302 (95% uncertainty interval: 338 174 876 to 371 610 802) new cases of injury globally, which increased to 520 710 288 (493 430 247 to 547 988 635) new cases in 2017. During this time, age-standardised incidence decreased non-significantly from 6824 (6534 to 7147) to 6763 (6412 to 7118) per 100 000. Between 1990 and 2017, age-standardised DALYs decreased from 4947 (4655 to 5233) per 100 000 to 3267 (3058 to 3505). Interpretation Injuries are an important cause of health loss globally, though mortality has declined between 1990 and 2017. Future research in injury burden should focus on prevention in high-burden populations, improving data collection and ensuring access to medical care.Peer reviewe

Genetic Diversity of Mycobacterium tuberculosis Complex Isolated from Tuberculosis Patients in Bahir Dar City and Its Surroundings, Northwest Ethiopia

The knowledge of the diversity of strains of Mycobacterium tuberculosis complex (MTBC) species in a specific geographical region can contribute to the control of tuberculosis (TB). This study was conducted to identify the MTBC isolates to the species and spoligotype international type (SIT) level by spoligotyping. A total of 168 MTBC isolates were recovered from TB patients, spoligotyped, and their patterns were compared with those of the strains registered in the SITVIT2 database. Of 168 isolates spoligotyped, 89 patterns were identified. Ninety-eight isolates were clustered into 19 strain groups with clustering percentage of 58.3%. Forty-four strains matched the preexisting SITs in the SITVIT2 database. The dominant strains were SIT289, SIT134, and SIT3411, comprising 16.7% (28/168), 7.14% (12/168), and 4.76% (8/168) of the isolates, respectively. Euro-American (51.2%), East-African-Indian (34.5%), and M. africanum (9.52%) were the major lineages identified. Two strains of M. bovis were isolated from TB lymphadenitis cases. The high percentage of clustered strains of M. tuberculosis could suggest that a small number of lineages of M. tuberculosis are causing the disease in the area while isolation of M. bovis could suggest its zoonotic potential. Additionally, identification of M. africanum requires further confirmation by tools with a better discriminatory power

Multivariable analysis of factors associated with SARS-CoV-2 co-infection with other respiratory viruses among ILI/SARI cases visited sentinel sites from January 2021 to June 2022, Ethiopia.

Multivariable analysis of factors associated with SARS-CoV-2 co-infection with other respiratory viruses among ILI/SARI cases visited sentinel sites from January 2021 to June 2022, Ethiopia.</p

Characteristics of patients with SARS-CoV-2 and other respiratory viruses’ co-detection.

Characteristics of patients with SARS-CoV-2 and other respiratory viruses’ co-detection.</p

Monthly trends of proportions of co-detection among SARS-CoV-2 positive cases from January 01, 2021, to June 30, 2022, Ethiopia.

Monthly trends of proportions of co-detection among SARS-CoV-2 positive cases from January 01, 2021, to June 30, 2022, Ethiopia.</p

Demographic characteristics of ILI/SARI cases visited sentinel sites from January 2021 to June 2022, Ethiopia.

Demographic characteristics of ILI/SARI cases visited sentinel sites from January 2021 to June 2022, Ethiopia.</p

Distribution of SARS-CoV-2 co-detection and mono-infections across SARI/ILI sentinel sites from January 01, 2021, to June 30, 2022, Ethiopia.

Distribution of SARS-CoV-2 co-detection and mono-infections across SARI/ILI sentinel sites from January 01, 2021, to June 30, 2022, Ethiopia.</p