Surveillance for Mosquitoborne Transmission of Zika Virus, New York City, NY, USA, 2016

A Portrait of Sentinel Surveillance Networks for Vector-Borne Diseases: A Scoping Review Supporting Sentinel Network Design

Vector-borne diseases (VBDs) are continuing to emerge globally, requiring new surveillance systems to follow increasing VBD risk for human populations. Sentinel surveillance is an approach that allows tracking of disease risk through time using limited resources. However, there is no consensus on how best to design a sentinel surveillance network in the context of VBDs. We conducted a scoping review to compare VBD sentinel surveillance systems worldwide with the aim of identifying key design features associated with effective networks. Overall, VBD surveillance networks were used most commonly for malaria, West Nile virus, and lymphatic filariasis. A total of 45 criteria for the selection of sentinel unit location were identified. Risk-based criteria were the most often used, and logistic regression showed that using risk-based criteria dependent on host animals is particularly correlated with surveillance system sensitivity (p < 0.018). We identify tools that could prove valuable for sentinel surveillance network design, including a standardized approach for evaluating surveillance systems and a tool to prioritize criteria for selecting optimal geographic locations for spatial sentinel units.

Zoonosis: Update on Existing and Emerging Vector-Borne Illnesses in the USA

PURPOSE OF REVIEW

This review describes mosquito- and tick-borne diseases found in the Western Hemisphere. It focuses on emerging diseases and recent geographic shifts in the presence of disease vectors.

RECENT FINDINGS

Mosquito and tick vectors have become more widespread as environmental conditions have become more favorable. Zika recently has emerged as a concern for fetal anomalies. West Nile Virus has become widespread. Lyme disease and other tick-borne diseases are more prevalent in areas previously inhospitable to these ticks.

SUMMARY

Healthcare providers must consider the possibility of mosquito- and tick-borne diseases in broader geographic areas and council patients traveling to endemic areas on precautions against these diseases. Treatment for suspected cases of serious tick-borne illnesses should not be delayed pending culture results.

The Spectrum of Developmental Disability with Zika Exposure: What Is Known, What Is Unknown, and Implications for Clinicians

Clinicians who treat children with neurodevelopmental disabilities may encounter infants with congenital Zika syndrome or those exposed to Zika virus (ZIKV), either in utero or postnatally, in their practice and may have questions about diagnosis, management, and prognosis. In this special report, we reviewed the current literature to provide a comprehensive understanding of the findings and needs of children exposed to ZIKV in utero and postnatally. The current literature is sparse, and thus, this review is preliminary. We found that infants and children exposed to ZIKV in utero have a variety of health and developmental outcomes that suggest a wide range of lifelong physical and developmental needs. Postnatal exposure does not seem to have significant long-lasting health or developmental effects. We provide a comprehensive examination of the current knowledge on health and developmental care needs in children exposed to Zika in utero and postnatally. This can serve as a guide for health care professionals on the management and public health implications of this newly recognized population.

Simulation of Legionnaires' disease prospective spatiotemporal cluster detection, Allegheny County, Pennsylvania, USA

Legionnaires’ disease (LD) incidence in the USA has quadrupled since 2000. Health departments must detect LD outbreaks quickly to identify and remediate sources. We tested the performance of a system to prospectively detect simulated LD outbreaks in Allegheny County, Pennsylvania, USA. We generated three simulated LD outbreaks based on published outbreaks. After verifying no significant clusters existed in surveillance data during 2014–2016, we embedded simulated outbreak-associated cases into 2016, assigning simulated residences and report dates. We mimicked daily analyses in 2016 using the prospective space-time permutation scan statistic to detect clusters of ⩽30 and ⩽180 days using 365-day and 730-day baseline periods, respectively. We used recurrence interval (RI) thresholds of ⩾20, ⩾100 and ⩾365 days to define significant signals. We calculated sensitivity, specificity and positive and negative predictive values for daily analyses, separately for each embedded outbreak. Two large, simulated cooling tower-associated outbreaks were detected. As the RI threshold was increased, sensitivity and negative predictive value decreased, while positive predictive value and specificity increased. A small, simulated potable water-associated outbreak was not detected. Use of a RI threshold of ⩾100 days minimised time-to-detection while maximizing positive predictive value. Health departments should consider using this system to detect community-acquired LD outbreaks.

Public Health Surveillance for Zika Virus: Data Interpretation and Report Validity

Zika virus provides an example for which public health surveillance is based primarily on health care provider notifications to health departments of potential cases. This case-based surveillance is commonly used to understand the spread of disease in a population. However, case-based surveillance is often biased-whether testing is done and which tests are used and the accuracy of the results depend on a variety of factors including test availability, patient demand, perceptions of transmission, and patient and provider awareness, leading to surveillance artifacts that can provide misleading information on the spread of a disease in a population and have significant public health practice implications. To better understand this challenge, we first summarize the process that health departments use to generate surveillance reports, then describe factors influencing testing and reporting patterns at the patient, provider, and contextual level. We then describe public health activities, including active surveillance, that influence both patient and provider behavior as well as surveillance reports, and conclude with a discussion about the interpretation of surveillance data and approaches that could improve the validity of surveillance reports.

Identifying Areas at Greatest Risk for Recent Zika Virus Importation - New York City, 2016

INTRODUCTION

The New York City Department of Health and Mental Hygiene sought to detect and minimize the risk of local, mosquito-borne Zika virus (ZIKV) transmission. We modeled areas at greatest risk for recent ZIKV importation, in the context of spatially biased ZIKV case ascertainment and no data on the local spatial distribution of persons arriving from ZIKV-affected countries.

METHODS

For each of 14 weeks during June-September 2016, we used logistic regression to model the census tract-level presence of any ZIKV cases in the prior month, using eight covariates from static sociodemographic census data and the latest surveillance data, restricting to census tracts with any ZIKV testing in the prior month. To assess whether the model discriminated better than random between census tracts with and without recent cases, we compared the area under the receiver operating characteristic (ROC) curve for each week's fitted model versus an intercept-only model applied to cross-validated data. For weeks where the ROC contrast test was significant at P < 0.05, we output and mapped the model-predicted individual probabilities for all census tracts, including those with no recent testing.

RESULTS

The ROC contrast test was significant for 8 of 14 weekly analyses. No covariates were consistently associated with the presence of recent cases. Modeled risk areas fluctuated across these 8 weeks, with Spearman correlation coefficients ranging from 0.30 to 0.93, all P < 0.0001. Areas in the Bronx and upper Manhattan were in the highest risk decile as of late June, while as of late August, the greatest risk shifted to eastern Brooklyn.

CONCLUSION

We used observable characteristics of areas with recent, known travel-associated ZIKV cases to identify similar areas with no observed cases that might also be at-risk each week. Findings were used to target public education and Aedes spp. mosquito surveillance and control. These methods are applicable to other conditions for which biased case ascertainment is suspected and knowledge of how cases are geographically distributed is important for targeting public health activities.