Background: Meningitis is associated with substantial morbidity and mortality, particularly in the first three months of life. Methods: We conducted a retrospective review of patients <90 days of age with meningitis at Texas Children’s Hospital from 2010–2017. Cases were confirmed using the National Healthcare Safety Network (NHSN) definition of meningitis. Results: Among 694 infants with meningitis, the most common etiology was viral (n = 351; 51%), primarily caused by enterovirus (n = 332; 95%). A quarter of cases were caused by bacterial infections (n = 190; 27%). The most common cause of bacterial meningitis was group B Streptococcus (GBS, n = 60; 32%), followed by Gram-negative rods other than E. coli (n = 40; 21%), and E. coli (n = 37; 19%). The majority of Gram-negative organisms (63%) were resistant to ampicillin, and nearly one-fourth of Gram-negative rods (23%) other than E. coli and 2 (6%) E. coli isolates were resistant to third-generation cephalosporins. Significant risk factors for bacterial meningitis were early preterm birth and the Black race. Conclusions: Enteroviruses most commonly caused viral meningitis in infants; GBS was the most common bacterial cause despite universal screening and intrapartum prophylaxis. The emergence of MRSA and resistance to third-generation cephalosporins in Gram-negative bacterial meningitis challenges the options for empirical antimicrobial therapy.

Introduction: Homelessness is a public health problem, and persons experiencing homelessness are a vulnerable population. Estimates of the number of persons experiencing homelessness inform funding allocations and services planning and directly determine the ability of a community to intervene effectively in homelessness. The point-in-time (PIT) count presents a logistical problem in large urban areas, particularly those covering a vast geographical area. Materials and Methods: Working together, academia, local government, and community organizations improved the methodology for the count. Specific enhancements include use of incident command system (ICS), increased number of staging areas/teams, specialized outreach and Special Weapons and Tactics teams, and day-after surveying to collect demographic information. Results: This collaboration and enhanced methodology resulted in a more accurate estimate of the number of persons experiencing homelessness and allowed comparison of findings for 4 years. While initial results showed an increase due to improved counting, the number of persons experiencing homelessness counted for the subsequent years showed significant decrease during the same time period as a “housing first” campaign was implemented. The collaboration also built capacity in each sector: The health department used ICS as a training opportunity; the academics enhanced their community health efforts; the service sector was taught and implemented more rigorous quantitative methods; and the community was exposed to public health as a pragmatic and effective discipline. Practical Implications: Improvements made to increase the reliability of the PIT count can be adapted for use in other jurisdictions, leading to improved counts and better evaluation of progress in ending homelessness.

Human immunodeficiency virus 1 (HIV-1) is a retrovirus which has infected 90 million people and resulted in over 40 million deaths. Despite advances in diagnostics, treatment, and prophylaxis, HIV-1 continues to spread due to undiagnosed and untreated infections. Traditional monitoring methods are ineffective when access to testing is limited or people do not seek care, particularly given the long period between infection and symptom onset, allowing undetected transmission to continue. Here, we use a hybrid-capture sequencing approach to track HIV-1 signal in municipal wastewater in 15 different cities over nearly 3 years. We obtain near-complete genomic coverage of HIV-1, enabling detailed genomic analysis. Surprisingly, there are a substantial number of research-associated retroviral vector sequences recovered. Using computational competitive mapping, we identify specific genomic regions that differentiate authentic HIV-1 from vector-derived inputs. In an exploratory analysis of sites with available clinical data, wastewater-derived circulating HIV-1 reads show a positive correlation with community-level HIV diagnosed prevalence that was robust to exclusion of individual high-prevalence sites. This study identifies lentiviral vector contamination as a confounding factor in wastewater HIV-1 detection, recovers authentic circulating HIV-1 signal through an original classification framework, and provides initial evidence that the resulting signal tracks community HIV burden.

COVID-19 reached the US in January, 2020, but state and local case detection efforts varied in timing and scale. We conducted a state-level ecological analysis of COVID-19 epidemiology alongside CDC influenza surveillance data and policy timelines. Our findings show wide variation in COVID-19 case detection and influenza-like-illness activity between states.