Disparities in Zika Virus Testing and Incidence Among Women of Reproductive Age—New York City, 2016. Issue 6 (November 2018) - Lee, Christopher T.; Greene, Sharon K.; Baumgartner, Jennifer; Fine, Anne
Abstract : Context: The New York City Department of Health and Mental Hygiene (NYC DOHMH) performs surveillance for reportable diseases, including Zika virus (ZIKV) infection and disease, to inform public health responses. Incidence rates of other mosquito-borne diseases related to international travel are associated with census tract poverty level in NYC, suggesting that high poverty areas might be at higher risk for ZIKV infections. Objectives: We assessed ZIKV testing rates and incidence of travel-associated infection among reproductive age women in NYC to identify areas with high incidence and low testing rates and assess the effectiveness of public health interventions. Design: We analyzed geocoded ZIKV surveillance data collected by NYC DOHMH. Women aged 15 to 44 years tested during January-July 2016 (n = 4733) were assigned to census tracts, which we grouped by poverty level and quartile of the number of persons born in countries or territories with mosquito-borne ZIKV transmission as a proxy for risk of travel to these areas. We calculated crude ZIKV testing rates, incidence rates, and incidence rate ratios (IRRs). Setting: New York City. Results: Eight percent of patients (n = 376) tested had evidence of ZIKV infection. Cumulative incidence was higher both in areas with higher versus lower poverty levels (IRR = 2.4; 95% confidence interval [CI], 2.0-3.0) and in areas with the largest versus smallest populations of persons born in countries or territories with mosquito-borne ZIKV transmission (IRR = 11.3; 95% CI, 6.2-20.7). Initially, ZIKV testing rates were lowest in higher poverty areas with the largest populations of persons born in countries or territories with mosquito-borne ZIKV transmission (15/100 000), but following targeted interventions, testing rates were highest in these areas (80/100 000). Conclusions: Geocoded data enabled us to identify communities with low testing but high ZIKV incidence rates, intervene to promote testing and reduce barriers to testing, and measure changes in testing rates.