Used as recommended, acaricide barrier sprays do not significantly reduce the household risk of tick exposure or incidence of tick-borne disease. Measures for preventing tick-borne diseases should be evaluated against human outcomes to confirm effectiveness.

On August 16, 2022, this report was posted as an MMWR Early Release on the MMWR website (https://www.cdc.gov/mmwr).On July 18, 2022, the New York State Department of Health (NYSDOH) notified CDC of detection of poliovirus type 2 in stool specimens from an unvaccinated immunocompetent young adult from Rockland County, New York, who was experiencing acute flaccid weakness. The patient initially experienced fever, neck stiffness, gastrointestinal symptoms, and limb weakness. The patient was hospitalized with possible acute flaccid myelitis (AFM). Vaccine-derived poliovirus type 2 (VDPV2) was detected in stool specimens obtained on days 11 and 12 after initial symptom onset. To date, related Sabin-like type 2 polioviruses have been detected in wastewater* in the patient's county of residence and in neighboring Orange County up to 25 days before (from samples originally collected for SARS-CoV-2 wastewater monitoring) and 41 days after the patient's symptom onset. The last U.S. case of polio caused by wild poliovirus occurred in 1979, and the World Health Organization Region of the Americas was declared polio-free in 1994. This report describes the second identification of community transmission of poliovirus in the United States since 1979; the previous instance, in 2005, was a type 1 VDPV (1). The occurrence of this case, combined with the identification of poliovirus in wastewater in neighboring Orange County, underscores the importance of maintaining high vaccination coverage to prevent paralytic polio in persons of all ages.

Blacklegged ticks, Ixodes scapularis Say, were collected from 27 sites in eight New York State counties from 2003 to 2006 to determine the prevalence and distribution of tick-borne pathogens in public-use areas over a 4-yr period. In total, 11,204 I. scapularis (3,300 nymphs and 7,904 adults) were individually analyzed using polymerase chain reaction to detect the presence of Borrelia burgdorferi (causative agent of Lyme disease), Anaplasma phagocytophilum (formerly Ehrlichia phagocytophila, causative agent of human granulocytic anaplasmosis), and Babesia microti (causative agent of human babesiosis). Overall prevalence of B. burgdorferi, A. phagocytophilum, and B. microti was 14.4, 6.5, and 2.7% in nymphs and 45.7, 12.3, and 2.5% in adult ticks, respectively. Rates varied geographically and temporally during the time period examined, and were related to measurements of tick density. Average rate ofpolymicrobial infection for nymphs and adults, respectively, was 1.5 and 8.5% overall, with 0.5 and 6.3% coinfection of B. burgdorferi and A. phagocytophilum, 1.0 and 1.5% B. burgdorferi and B. microti, and 0.05 and 0.6% A. phagocytophilum and B. microti. Thirty-three individual adult ticks from seven study sites in Westchester, Putnam, Dutchess, and Rockland counties tested positive for simultaneous infection with all three agents by multiplex polymerase chain reaction assay.

West Nile virus (WNV; Flaviviridae : Flavivirus ) is a widely distributed arthropod-borne virus that has negatively affected human health and animal populations. WNV infection rates of mosquitoes and human cases have been shown to be correlated with climate. However, previous studies have been conducted at a variety of spatial and temporal scales, and the scale-dependence of these relationships has been understudied. We tested the hypothesis that climate variables are important to understand these relationships at all spatial scales. We analyzed the influence of climate on WNV infection rate of mosquitoes and number of human cases in New York and Connecticut using Random Forests, a machine learning technique. During model development, 66 climate-related variables based on temperature, precipitation and soil moisture were tested for predictive skill. We also included 20–21 non-climatic variables to account for known environmental effects (e.g., land cover and human population), surveillance related information (e.g., relative mosquito abundance), and to assess the potential explanatory power of other relevant factors (e.g., presence of wastewater treatment plants). Random forest models were used to identify the most important climate variables for explaining spatial-temporal variation in mosquito infection rates (abbreviated as MLE ). The results of the cross-validation support our hypothesis that climate variables improve the predictive skill for MLE at county- and trap-scales and for human cases at the county-scale. Of the climate-related variables selected, mean minimum temperature from July–September was selected in all analyses, and soil moisture was selected for the mosquito county-scale analysis. Models demonstrated predictive skill, but still over- and under-estimated WNV MLE and numbers of human cases. Models at fine spatial scales had lower absolute errors but had greater errors relative to the mean infection rates.

No abstract

Southern strains are undergoing amplification, perpetuation, and overwintering in New York.

The population densities of many organisms have changed dramatically in recent history. Increases in the population density of medically relevant organisms are of particular importance to public health as they are often correlated with the emergence of infectious diseases in human populations. Our aim is to delineate increases in density of a common disease vector in North America, the blacklegged tick, and to identify the environmental factors correlated with these population dynamics. Empirical data that capture the growth of a population are often necessary to identify environmental factors associated with these dynamics. We analyzed temporally- and spatially-structured field collected data in a geographical information systems framework to describe the population growth of blacklegged ticks (Ixodes scapularis) and to identify environmental and climatic factors correlated with these dynamics. The density of the ticks increased throughout the study’s temporal and spatial ranges. Tick density increases were positively correlated with mild temperatures, low precipitation, low forest cover, and high urbanization. Importantly, models that accounted for these environmental factors accurately forecast future tick densities across the region. Tick density increased annually along the south-to-north gradient. These trends parallel the increases in human incidences of diseases commonly vectored by I. scapularis. For example, I. scapularis densities are correlated with human Lyme disease incidence, albeit in a non-linear manner that disappears at low tick densities, potentially indicating that a threshold tick density is needed to support epidemiologically-relevant levels of the Lyme disease bacterium. Our results demonstrate a connection between the biogeography of this species and public health.

Migration is a primary force of biological evolution that alters allele frequencies and introduces novel genetic variants into populations. Recent migration has been proposed as the cause of the emergence of many infectious diseases, including those carried by blacklegged ticks in North America. Populations of blacklegged ticks have established and flourished in areas of North America previously thought to be devoid of this species. The recent discovery of these populations of blacklegged ticks may have resulted from either in situ growth of long-established populations that were maintained at very low densities or by migration and colonization from established populations. These alternative evolutionary hypotheses were investigated using Bayesian phylogeographic approaches to infer the origin and migratory history of recently detected blacklegged tick populations in the Northeastern United States. The data and results indicate that newly detected tick populations are not the product of in situ population growth from a previously established population but from recent colonization resulting in a geographic range expansion. This expansion in the geographic range proceeded primarily through progressive and local migration events from southern populations to proximate northern locations although long-distance migration events were also detected.