With a population of forty million and substantial geographic variation in sociodemographics and health services, California is an important setting in which to study disparities. Its population (37.5 percent White, 39.1 percent Latino, 5.3 percent Black, and 14.4 percent Asian) experienced 59,258 COVID-19 deaths through April 14, 2021-the most of any state. We analyzed California's racial/ethnic disparities in COVID-19 exposure risks, testing rates, test positivity, and case rates through October 2020, combining data from 15.4 million SARS-CoV-2 tests with subcounty exposure risk estimates from the American Community Survey. We defined "high-exposure-risk" households as those with one or more essential workers and fewer rooms than inhabitants. Latino people in California are 8.1 times more likely to live in high-exposure-risk households than White people (23.6 percent versus 2.9 percent), are overrepresented in cumulative cases (3,784 versus 1,112 per 100,000 people), and are underrepresented in cumulative testing (35,635 versus 48,930 per 100,000 people). These risks and outcomes were worse for Latino people than for members of other racial/ ethnic minority groups. Subcounty disparity analyses can inform targeting of interventions and resources, including community-based testing and vaccine access measures. Tracking COVID-19 disparities and developing equity-focused public health programming that mitigates the effects of systemic racism can help improve health outcomes among California's populations of color. T he COVID-19 pandemic in the US has disproportionately affected people with low socioeconomic status, as well as Black, Indigenous, and Latino people, 1-6 all of whom have experienced higher rates of cases, 7,8 hospitalizations, 1,9,10 and deaths. 8,9,11 As a state with a population of forty million with substantial county and regional variation in terms of dem-ographics, socioeconomic status, and health services, California is an important setting in which to study these disparities. As of April 14, 2021, California's 59,258 total COVID-19 deaths represented the highest number among all states, within a statewide population that is 37.5 percent White, 39.1 percent Latino, 5.3 percent Black, and 14.4 percent Asian. 12,13 Previous analyses of COVID-19 disparities in California have focused

This is the first confirmation of human disease associated with the SFGR 364D, which was likely transmitted by D. occidentalis. Although the patients described here presented with a single cutaneous eschar as the principal manifestation, the full spectrum of illness associated with 364D has yet to be determined. Possible infection with 364D or other SFGR should be confirmed through molecular techniques in patients who present with "spotless" Rocky Mountain spotted fever or have serum antibodies to R. rickettsii with group-specific assays.

Background: Plague, caused by the bacterium Yersinia pestis, is a public and wildlife health concern in California and the western United States. This study explores the spatial characteristics of positive plague samples in California and tests Maxent, a machine-learning method that can be used to develop niche-based models from presence-only data, for mapping the potential distribution of plague foci. Maxent models were constructed using geocoded seroprevalence data from surveillance of California ground squirrels (Spermophilus beecheyi) as case points and Worldclim bioclimatic data as predictor variables, and compared and validated using area under the receiver operating curve (AUC) statistics. Additionally, model results were compared to locations of positive and negative coyote (Canis latrans) samples, in order to determine the correlation between Maxent model predictions and areas of plague risk as determined via wild carnivore surveillance.

In 1993 Sin Nombre virus was recognized as the cause of hantavirus pulmonary syndrome (HPS) and the deer mouse (Peromyscus maniculatus) was identified as the reservoir host. Surveillance by the Centers for Disease Control and Prevention and state health departments includes investigation to determine the likely site(s) and activities that led to infection, an environmental assessment of the home and workplace, and possibly rodent trappings at these sites. As of December 31, 1998, there were 200 confirmed cases from 30 states (43% case-fatality ratio). The national HPS case registry was examined to determine the incubation period of HPS. Review of 11 case-patients with welldefined and isolated exposure to rodents suggests that the incubation period of HPS is 9 to 33 days, with a median of 14-17 days. Case investigations allow a better understanding of the incubation time of HPS and may define highrisk behaviors that can be targeted for intervention.

Ixodes pacificus, particularly the nymphal life stage, is the primary vector to humans of the Lyme disease agent Borrelia burgdorferi in California. During 2004, we collected I. pacificus nymphs from 78 woodland sites in ecologically diverse Mendocino County, which has a moderately high incidence of Lyme disease. Within this county, nymphal density was elevated in forested areas with a growing degree day range of 2,600-3,000 (10 degrees C base). Using a geographic information systems approach, we identified all areas in California sharing these environmental characteristics and thus projected to pose high acarologic risk of exposure to host-seeking nymphal ticks. Such areas were most commonly detected in the northwestern part of the state and along the Sierra Nevada foothills in the northeast, but the analysis also identified isolated areas with high acarologic risk in southern California. This mirrors the spatial distribution of endemic Lyme disease during 1993-2005; most cases occurred in counties to the northwest (58%) or northeast (26%), whereas fewer cases were reported from southern California (16%). Southern zip-codes from which Lyme disease cases had been reported were commonly located in close proximity to areas with high projected acarologic risk. Overall, Lyme disease incidence in zip code areas containing habitat with high projected acarologic risk was 10-fold higher than in zip code areas lacking such habitat and 27 times higher than for zip code areas without this habitat type within 50 km. A comparison of spatial Lyme disease incidence patterns based on county versus zip code units showed that calculating and displaying disease incidence at the zip code scale is a useful method to detect small, isolated areas with elevated disease risk that otherwise may go undetected.