COVID-19-associated deaths were reported in the United States (1). Understanding the demographic and clinical characteristics of decedents could inform medical and public health interventions focused on preventing COVID-19-associated mortality. This report describes decedents with laboratory-confirmed infection with SARS-CoV-2, the virus that causes COVID-19, using data from 1) the standardized CDC case-report form (case-based surveillance) (https://www.cdc.gov/coronavirus/2019-ncov/php/ reporting-pui.html) and 2) supplementary data (supplemental surveillance), such as underlying medical conditions and location of death, obtained through collaboration between CDC and 16 public health jurisdictions (15 states and New York City). Case-based surveillanceDemographic and clinical data about COVID-19 cases are reported to CDC from 50 states, the District of Columbia, New York City, and U.S. territories using a standardized case-report form (case-based surveillance) or in aggregate. Data on 52,166 deaths from 47 jurisdictions among persons with laboratoryconfirmed COVID-19 were reported individually to CDC via case-based surveillance during February 12-May 18, 2020. Among the 52,166 decedents, 55.4% were male, 79.6% were aged ≥65 years, 13.8% were Hispanic/Latino (Hispanic), 21.0% were black, 40.3% were white, 3.9% were Asian, 0.3% were American Indian/Alaska Native (AI/AN), 0.1% were Native Hawaiian or other Pacific Islander (NHPI), 2.6% were multiracial or other race, and race/ethnicity was unknown for 18.0%. (Table 1). Median decedent age was 78 years (interquartile range (IQR) = 67-87 years). Because information about underlying medical conditions was missing for the majority of these decedents (30,725; 58.9%), data regarding medical conditions were not analyzed further using the case-based surveillance data set. Because most decedents reported to the supplementary data program were also reported to case-based surveillance, no statistical comparisons of the decedent characteristics between the data sets were made. * Underlying medical conditions include cardiovascular disease (congenital heart disease, coronary artery disease, congestive heart failure, hypertension, cerebrovascular accident/stroke, valvular heart disease, conduction disorders or dysrhythmias, other cardiovascular disease); diabetes mellitus; chronic lung disease (chronic obstructive pulmonary disease/emphysema, asthma, tuberculosis, other chronic lung diseases); immunosuppression (cancer, human immunodeficiency virus (HIV) infection, identified as being immunosuppressed); chronic kidney disease (chronic kidney disease, end-stage renal disease, other kidney diseases); neurologic conditions (dementia, seizure disorder, other neurologic conditions); chronic liver disease (cirrhosis, alcoholic hepatitis, chronic liver disease, end-stage liver disease, hepatitis B, hepatitis C, nonalcoholic steatohepatitis, other chronic liver diseases); obesity (body mass index ≥30 kg/m 2 ). Information was collected from decedent medical records or death certificates. ...

Preventing transmission of SARS-CoV-2, the virus that causes coronavirus disease 2019 , in institutes of higher education presents a unique set of challenges because of the presence of congregate living settings and difficulty limiting socialization and group gatherings. Before August 2020, minimal data were available regarding COVID-19 outbreaks in these settings. On August 3, 2020, university A in North Carolina broadly opened campus for the first time since transitioning to primarily remote learning in March. Consistent with CDC guidance at that time (1,2), steps were taken to prevent the spread of SARS-CoV-2 on campus. During August 3-25, 670 laboratory-confirmed cases of COVID-19 were identified; 96% were among patients aged <22 years. Eighteen clusters of five or more epidemiologically linked cases within 14 days of one another were reported; 30% of cases were linked to a cluster. Student gatherings and congregate living settings, both on and off campus, likely contributed to the rapid spread of COVID-19 within the university community. On August 19, all university A classes transitioned to online, and additional mitigation efforts were implemented. At this point, 334 university A-associated COVID-19 cases had been reported to the local health department. The rapid increase in cases within 2 weeks of opening campus suggests that robust measures are needed to reduce transmission at institutes of higher education, including efforts to increase consistent use of masks, reduce the density of on-campus housing, increase testing for SARS-CoV-2, and discourage student gatherings.University A students returned to residence halls during August 3-9, 2020, and in-person classes began on August 10. Mitigation steps taken to prevent the spread of SARS-CoV-2 on campus included scheduling move-in appointments across a 1-week period, decreasing classroom density to facilitate physical distancing, and reducing maximum dining hall capacity and increasing takeout options. Students were required to sign an acknowledgment of community standards and university guidelines recommending daily symptom checks, * These authors contributed equally.

Seven rounds of mass drug administration (MDA) have been administered in Leogane, Haiti, an area hyperendemic for lymphatic filariasis (LF). Sentinel site surveys showed that the prevalence of microfilaremia was reduced to <1% from levels as high as 15.5%, suggesting that transmission had been reduced. A separate 30-cluster survey of 2- to 4-year-old children was conducted to determine if MDA interrupted transmission. Antigen and antifilarial antibody prevalence were 14.3% and 19.7%, respectively. Follow-up surveys were done in 6 villages, including those selected for the cluster survey, to assess risk factors related to continued LF transmission and to pinpoint hotspots of transmission. One hundred houses were mapped in each village using GPS-enabled PDAs, and then 30 houses and 10 alternates were chosen for testing. All individuals in selected houses were asked to participate in a short survey about participation in MDA, history of residence in Leogane and general knowledge of LF. Survey teams returned to the houses at night to collect blood for antigen testing, microfilaremia and Bm14 antibody testing and collected mosquitoes from these communities in parallel. Antigen prevalence was highly variable among the 6 villages, with the highest being 38.2% (Dampus) and the lowest being 2.9% (Corail Lemaire); overall antigen prevalence was 18.5%. Initial cluster surveys of 2- to 4-year-old children were not related to community antigen prevalence. Nearest neighbor analysis found evidence of clustering of infection suggesting that LF infection was focal in distribution. Antigen prevalence among individuals who were systematically noncompliant with the MDAs, i.e. they had never participated, was significantly higher than among compliant individuals (p<0.05). A logistic regression model found that of the factors examined for association with infection, only noncompliance was significantly associated with infection. Thus, continuing transmission of LF seems to be linked to rates of systematic noncompliance.

IMPORTANCE Contact tracing is a multistep process to limit SARS-CoV-2 transmission. Gaps in the process result in missed opportunities to prevent COVID-19.OBJECTIVE To quantify proportions of cases and their contacts reached by public health authorities and the amount of time needed to reach them and to compare the risk of a positive COVID-19 test result between contacts and the general public during 4-week assessment periods.

On September 22, 2020, this report was posted as an MMWR Early Release on the MMWR website (https://www.cdc.gov/mmwr). Contact tracing is a strategy implemented to minimize the spread of communicable diseases (1,2). Prompt contact tracing, testing, and self-quarantine can reduce the transmission of SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19) (3,4). Community engagement is important to encourage participation in and cooperation with SARS-CoV-2 contact tracing (5). Substantial investments have been made to scale up contact tracing for COVID-19 in the United States. During June 1-July 12, 2020, the incidence of COVID-19 cases in North Carolina increased 183%, from seven to 19 per 100,000 persons per day* (6). To assess local COVID-19 contact tracing implementation, data from two counties in North Carolina were analyzed during a period of high incidence. Health department staff members investigated 5,514 (77%) persons with COVID-19 in Mecklenburg County and 584 (99%) in Randolph Counties. No contacts were reported for 48% of cases in Mecklenburg and for 35% in Randolph. Among contacts provided, 25% in Mecklenburg and 48% in Randolph could not be reached by telephone and were classified as nonresponsive after at least one attempt on 3 consecutive days of failed attempts. The median interval from specimen collection from the index patient to notification of identified contacts was 6 days in both counties. Despite aggressive efforts by health department staff members to perform case investigations and contact tracing, many persons with COVID-19 did not report contacts, and many contacts were not reached. These findings indicate that improved timeliness of contact tracing, community engagement, and increased use of community-wide mitigation are needed to interrupt SARS-CoV-2 transmission. Routinely collected case investigation and contact tracing data from June 1-30, 2020, for Mecklenburg, and from June 15-July 12, 2020, for Randolph counties were analyzed. Case investigations were conducted for persons with laboratoryconfirmed COVID-19, including the elicitation of persons potentially exposed to the index patient (3). Contact tracing was performed for persons identified as close contacts and included inquiry about COVID-19-compatible symptoms † and instructions to self-quarantine for 14 days since last exposure (3). Health

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In this article, drawing on interviews with women and men in same sex relationships who have experienced domestic violence, we explore the ways in which recognition of domestic violence can be hampered by public stories about the phenomenon and practices of love. Public stories construct domestic violence as a gendered, heterosexual phenomenon that is predominantly physical in nature. Victims of domestic violence are also constructed as 'other' , weak and passive. In addition, we argue that practices of love obfuscate practices of violence; and can also result in victim/survivors constructing themselves as stronger than the perpetrator who needs their care.