Abstract
Rapid detection of increases in HIV transmission enables targeted outbreak response efforts to reduce the number of new infections. We analyzed US HIV surveillance data and identified spatiotemporal clusters of diagnoses. This systematic method can help target timely investigations and preventive interventions for maximum public health benefit.
Highlights
Rapid detection of increases in HIV transmission enables targeted outbreak response efforts to reduce the number of new infections
The Study We reviewed non–HIV outbreak detection literature and methods employed by disease and syndromic surveillance programs at Centers for Disease Control and Prevention (CDC) and in several state and local health departments
IDU-attributable diagnoses constitute a small proportion of total diagnoses, so the ability to identify potential IDU transmission clusters by analyzing IDU-attributable diagnoses separately is a strength of this method
Summary
HIV symptom onset and diagnosis can be delayed compared with other infectious diseases, so we varied frames for batching data and manually compared method outputs to determine optimal parameters based on epidemiologists’ assessments of the most concerning clusters This systematic method detects increases in HIV diagnoses above expected baselines (i.e., alerts) in specified geographic areas. We applied this method to NHSS data reported from all 50 US states and the District of Columbia, examining the numbers of cases by state and county or countyequivalent (e.g., borough, parish; hereafter, collectively referred to as “county” and including the District of Columbia). Using the exact Pearson test for homogeneity, we determined that alerting counties were disproportionately located in the Northeast
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