Optimized quantification of intra-host viral diversity in SARS-CoV-2 and influenza virus sequence data.

High error rates of viral RNA-dependent RNA polymerases lead to diverse intra-host viral populations during infection. Errors made during replication that are not strongly deleterious to the virus can lead to the generation of minority variants. However, accurate detection of minority variants in viral sequence data is complicated by errors introduced during sample preparation and data analysis. We used synthetic RNA controls and simulated data to test seven variant-calling tools across a range of allele frequencies and simulated coverages. We show that choice of variant caller and use of replicate sequencing have the most significant impact on single-nucleotide variant (SNV) discovery and demonstrate how both allele frequency and coverage thresholds impact both false discovery and false-negative rates. When replicates are not available, using a combination of multiple callers with more stringent cutoffs is recommended. We use these parameters to find minority variants in sequencing data from SARS-CoV-2 clinical specimens and provide guidance for studies of intra-host viral diversity using either single replicate data or data from technical replicates. Our study provides a framework for rigorous assessment of technical factors that impact SNV identification in viral samples and establishes heuristics that will inform and improve future studies of intra-host variation, viral diversity, and viral evolution. IMPORTANCE When viruses replicate inside a host cell, the virus replication machinery makes mistakes. Over time, these mistakes create mutations that result in a diverse population of viruses inside the host. Mutations that are neither lethal to the virus nor strongly beneficial can lead to minority variants that are minor members of the virus population. However, preparing samples for sequencing can also introduce errors that resemble minority variants, resulting in the inclusion of false-positive data if not filtered correctly. In this study, we aimed to determine the best methods for identification and quantification of these minority variants by testing the performance of seven commonly used variant-calling tools. We used simulated and synthetic data to test their performance against a true set of variants and then used these studies to inform variant identification in data from SARS-CoV-2 clinical specimens. Together, analyses of our data provide extensive guidance for future studies of viral diversity and evolution.

Optimized Quantification of Intrahost Viral Diversity in SARS-CoV-2 and Influenza Virus Sequence Data.

High error rates of viral RNA-dependent RNA polymerases lead to diverse intra-host viral populations during infection. Errors made during replication that are not strongly deleterious to the virus can lead to the generation of minority variants. However, accurate detection of minority variants in viral sequence data is complicated by errors introduced during sample preparation and data analysis. We used synthetic RNA controls and simulated data to test seven variant calling tools across a range of allele frequencies and simulated coverages. We show that choice of variant caller, and use of replicate sequencing have the most significant impact on single nucleotide variant (SNV) discovery and demonstrate how both allele frequency and coverage thresholds impact both false discovery and false negative rates. We use these parameters to find minority variants in sequencing data from SARS-CoV-2 clinical specimens and provide guidance for studies of intrahost viral diversity using either single replicate data or data from technical replicates. Our study provides a framework for rigorous assessment of technical factors that impact SNV identification in viral samples and establishes heuristics that will inform and improve future studies of intrahost variation, viral diversity, and viral evolution. IMPORTANCE: When viruses replicate inside a host, the virus replication machinery makes mistakes. Over time, these mistakes create mutations that result in a diverse population of viruses inside the host. Mutations that are neither lethal to the virus, nor strongly beneficial, can lead to minority variants that are minor members of the virus population. However, preparing samples for sequencing can also introduce errors that resemble minority variants, resulting in inclusion of false positive data if not filtered correctly. In this study, we aimed to determine the best methods for identification and quantification of these minority variants by testing the performance of seven commonly used variant calling tools. We used simulated and synthetic data to test their performance against a true set of variants, and then used these studies to inform variant identification in data from clinical SARS-CoV-2 clinical specimens. Together, analyses of our data provide extensive guidance for future studies of viral diversity and evolution.

Baseline Trachoma Surveys in Kaskazini A and Micheweni Districts of Zanzibar: Results of Two Population-Based Prevalence Surveys Conducted with the Global Trachoma Mapping Project.

PURPOSE: Based on health care records and trachoma rapid assessments, trachoma was suspected to be endemic in Kaskazini A and Micheweni districts of Zanzibar. This study aimed to investigate the prevalence of trachomatous inflammation-follicular (TF), and trachomatous trichiasis (TT) in each of those districts. METHODS: The survey was undertaken in Kaskazini A and Micheweni districts on Unguja and Pemba Islands, respectively. A multi-stage cluster random sampling design was applied, whereby 25 census enumeration areas (clusters) and 30 households per cluster were included. Consenting eligible participants (children aged 1-9 years and people aged 15 years and older) were examined for trachoma using the World Health Organization simplified grading system. RESULTS: A total of 1673 households were surveyed and 6407 participants (98.0% of those enumerated) were examined for trachoma. Examinees included a total of 2825 children aged 1-9 years and 3582 people aged 15 years and older. TF prevalence in 1-9-year-olds was 2.7% (95% confidence interval, CI, 2.7-4.1%) in Kazkazini A and 11.4% (95% CI 6.6-16.5%) in Micheweni. Among people aged 15 years and older, TT prevalence was 0.01% (95% CI 0.00-0.04%) in Kazkazini A and 0.21% (95% CI 0.08-0.39%) in Micheweni. CONCLUSION: Trachoma is a public health problem in Micheweni district, where implementation of all four components of the SAFE strategy (surgery, antibiotics, facial cleanliness, and environmental improvement), including mass drug administration with azithromycin, is required. These findings will facilitate planning for trachoma elimination.

Obstetric outcome in grand multipara in the United Arab Emirates. A case control study.

OBJECTIVE: To compare the obstetric outcome in grand multiparous and low parous United Arab Emirates women. METHOD: The records of 418 grand multiparous women (study group), defined as having had given birth at least 5 times after completed 22 weeks gestational age, and 418 women of parity 2-4 (control group) were reviewed. RESULTS: Mean parity in the study group was 7.9 +/- 2.4. The number of subjects who attended for antenatal care and the number of visits were equal in both groups. Diabetes mellitus (both overt and gestational) was significantly more common in the study group (p < 0.0001) but there was no significant increase in the incidence of other obstetric complications nor in perinatal mortality rate. Babies of grand multiparous mothers required significantly more admissions to special care unit because of maternal diabetes mellitus (p < 0.0002). CONCLUSION: Diabetes mellitus was more common in grand multiparous United Arab Emirates women but the incidence of other obstetric complications was similar to lower parity women.