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      Update: Public Health Response to the Coronavirus Disease 2019 Outbreak — United States, February 24, 2020

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      , MD 1 , , CDC COVID-19 Response Team
      Morbidity and Mortality Weekly Report
      Centers for Disease Control and Prevention

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          Abstract

          An outbreak of coronavirus disease 2019 (COVID-19) caused by the 2019 novel coronavirus (SARS-CoV-2) began in Wuhan, Hubei Province, China in December 2019, and has spread throughout China and to 31 other countries and territories, including the United States ( 1 ). As of February 23, 2020, there were 76,936 reported cases in mainland China and 1,875 cases in locations outside mainland China ( 1 ). There have been 2,462 associated deaths worldwide; no deaths have been reported in the United States. Fourteen cases have been diagnosed in the United States, and an additional 39 cases have occurred among repatriated persons from high-risk settings, for a current total of 53 cases within the United States. This report summarizes the aggressive measures ( 2 , 3 ) that CDC, state and local health departments, multiple other federal agencies, and other partners are implementing to slow and try to contain transmission of COVID-19 in the United States. These measures require the identification of cases and contacts of persons with COVID-19 in the United States and the recommended assessment, monitoring, and care of travelers arriving from areas with substantial COVID-19 transmission. Although these measures might not prevent widespread transmission of the virus in the United States, they are being implemented to 1) slow the spread of illness; 2) provide time to better prepare state and local health departments, health care systems, businesses, educational organizations, and the general public in the event that widespread transmission occurs; and 3) better characterize COVID-19 to guide public health recommendations and the development and deployment of medical countermeasures, including diagnostics, therapeutics, and vaccines. U.S. public health authorities are monitoring the situation closely, and CDC is coordinating efforts with the World Health Organization (WHO) and other global partners. Interim guidance is available at https://www.cdc.gov/coronavirus/index.html. As more is learned about this novel virus and this outbreak, CDC will rapidly incorporate new knowledge into guidance for action by CDC, state and local health departments, health care providers, and communities. Person-to-person spread of COVID-19 appears to occur mainly by respiratory transmission. How easily the virus is transmitted between persons is currently unclear. Signs and symptoms of COVID-19 include fever, cough, and shortness of breath ( 4 ). Based on the incubation period of illness for Middle East respiratory syndrome (MERS) and severe acute respiratory syndrome (SARS) coronaviruses, as well as observational data from reports of travel-related COVID-19, CDC estimates that symptoms of COVID-19 occur within 2–14 days after exposure. Preliminary data suggest that older adults and persons with underlying health conditions or compromised immune systems might be at greater risk for severe illness from this virus ( 5 ). COVID-19 Cases in the United States As of February 23, 14 COVID-19 cases had been diagnosed in the following six states: Arizona (one case), California (eight), Illinois (two), Massachusetts (one), Washington (one), and Wisconsin (one). Twelve of these 14 cases were related to travel to China, and two cases occurred through person-to-person transmission to close household contacts of a person with confirmed COVID-19. An additional 39 cases were reported among repatriated U.S. citizens, residents, and their families returning from Hubei province, China (three), and from the Diamond Princess cruise ship that was docked in Yokohama, Japan (36). Thus, there have been 53 cases within the United States. No deaths have been reported in the United States. CDC Public Health Response As of February 24, 2020, a total of 1,336 CDC staff members have been involved in the COVID-19 response, including clinicians (i.e., physicians, nurses, and pharmacists), epidemiologists, veterinarians, laboratorians, communicators, data scientists and modelers, and coordination staff members. Of these CDC staff members, 497 (37%) have been deployed to 39 locations in the United States and internationally, including CDC quarantine stations at U.S. ports of entry, state and local health departments, hospitals, and U.S. military bases that are housing quarantined persons, as well as WHO and ministries of health around the world. CDC staff members are working with state, local, tribal, and territorial health departments and other public health authorities to assist with case identification, contact tracing, evaluation of persons under investigation (PUI) for COVID-19,* and medical management of cases; and with academic partners to understand the virulence, risk for transmission, and other characteristics of this novel virus. CDC teams are working with the Department of Homeland Security at 11 airports where all flights from China are being directed to screen travelers returning to the United States, and to refer them to U.S. health departments for oversight of self-monitoring. CDC is also working with other agencies of the U.S. government including the U.S. Department of Defense; multiple operational divisions with the U.S. Department of Health and Human Services, including the Assistant Secretary for Preparedness and Response and the Administration for Children and Families; and the U.S. Department of State to safely evacuate U.S. citizens, residents, and their families to the United States from international locations where there is substantial, sustained transmission of COVID-19, and to house them and monitor their health during a 14-day quarantine period. Specific guidance has been developed and posted online for health care settings, including for patient management; infection control and prevention; laboratory testing; environmental cleaning; worker safety; and international travel. † Guidance is updated as more is learned. To prepare for the possibility of community spread of COVID-19, CDC has developed tailored guidance and communications materials for communities, health care settings, public health, laboratories, schools, and businesses. Chinese and Spanish versions of certain documents are available. Information for travelers. Several recent travel notices have been posted by CDC to inform travelers and clinicians about current health issues that could affect travelers’ health. § A Level 3 travel notice (avoid all nonessential travel) for China has been in effect since January 27. On February 19, Level 1 travel notices (practice usual precautions) for travelers to Hong Kong and Japan were posted. On February 22, the Level 1 travel notice for Japan was raised to Level 2 (practice enhanced precautions). A Level 2 travel notice was posted for South Korea on February 22, which was updated to Level 3 on February 24. Level 1 travel notices were posted for Iran and Italy on February 23, and then updated to Level 2 on February 24. In addition, CDC has posted information for travelers regarding apparent community transmission in Singapore, Taiwan, Thailand, and Vietnam, and recommendations for persons to reconsider cruise ship voyages in Asia. Airport screening. As of February 23, a total of 46,016 air travelers had been screened at the 11 U.S. airports to which all flights from China are being directed. Since February 2, travelers to the United States who have been in China in the preceding 14 days have been limited to U.S. citizens and lawful permanent residents and others as outlined in a presidential proclamation. ¶ Incoming passengers are screened for fever, cough, and shortness of breath. Any travelers with signs or symptoms of illness receive a more comprehensive public health assessment. As of February 23, 11 travelers were referred to a hospital and tested for infection; one tested positive and was isolated and managed medically. Seventeen travelers were quarantined for 14 days because of travel from Hubei Province, China, an area that was designated as high risk for exposure to COVID-19**; 13 of these 17 have completed their quarantine period. Persons under investigation (PUIs). Recognizing persons at risk for COVID-19 is a critical component of identifying cases and preventing further transmission. CDC has responded to clinical inquiries from public health officials, health care providers, and repatriation teams to evaluate and test PUIs in the United States for COVID-19 following CDC guidance. As of February 23, 479 persons from 43 states and territories had been or are being tested for COVID-19; 14 (3%) had a positive test, 412 (86%) had a negative test, and 53 (11%) test results are pending. Laboratory testing. As part of laboratory surge capacity for the response, CDC laboratories are testing for SARS-CoV-2 to assist with diagnosis of COVID-19. During January 18–February 23, CDC laboratories used real-time reverse transcription–polymerase chain reaction (RT-PCR) to test 2,620 specimens from 1,007 persons for SARS-CoV-2. Some additional testing is performed at selected state and other public health laboratories, with confirmatory testing at CDC. CDC is developing a serologic test to assist with surveillance for SARS-CoV-2 circulation in the U.S. population. The test detects antibodies (immunoglobulin [Ig]G, IgA, and IgM) indicating SARS-COV-2 virus exposure or past infection. In addition, CDC laboratories are developing assays to detect SARS-CoV-2 viral RNA and antigens in tissue specimens. Finally, following CDC’s establishment of SARS-CoV-2 in cell culture, CDC shared virus isolates with the Biodefense and Emerging Infections Research Resources Repository to securely distribute isolates to U.S. public health and academic institutions for additional research, including vaccine development. Repatriation flights from areas with substantial COVID-19 transmission. During January 29–February 6, the U.S. government repatriated 808 U.S. citizens, residents, and their families from Hubei Province, China, on five chartered flights. At the time of departure, all travelers were free of symptoms for COVID-19 (fever or feverishness, cough, difficulty breathing). After arriving in the United States, the repatriated travelers were quarantined for 14 days at one of five U.S. military bases. CDC and U.S. government staff members monitored these travelers’ health. As of February 23, 28 (3%) of these persons developed COVID-19-related symptoms and were evaluated for infection; three were found to be positive for SARS-CoV-2 and were referred for medical care and isolation. As of February 24, the remaining 805 travelers had completed their 14-day quarantine. On February 3, passengers and crew of the Diamond Princess cruise ship were quarantined off Yokohama, Japan; a passenger who had recently disembarked in Hong Kong was confirmed to have COVID-19, and ongoing transmission was identified on the ship. By February 16, a total of 355 cases of COVID-19 had been identified among passengers and crew, †† including 67 U.S. citizens or residents. As a result, during February 16–17, the U.S. government assisted in the repatriation of 329 U.S. citizens or residents from the ship. These travelers returned on two chartered flights. As of February 23, 36 (11%) of these repatriated persons had tested positive for SARS-CoV-2 and are under appropriate medical supervision. The remaining repatriated persons are in quarantine for 14 days. CDC is working with the U.S. embassy in Japan and the Japanese government to support U.S. passengers and crew who remained in Japan. Discussion COVID-19 is a serious public health threat. Cases of COVID-19 have been diagnosed in the United States, primarily in travelers from China and quarantined repatriates, and also in two close contacts of COVID-19 patients. Currently, COVID-19 is not recognized to be spreading in U.S. communities. If sustained transmission in U.S. communities is identified, the U.S. response strategy will enhance implementation of actions to slow spread in communities ( 2 , 6 ). Implementation of basic precautions of infection control and prevention, including staying home when ill and practicing respiratory and hand hygiene will become increasingly important. Community-level nonpharmaceutical intervention might include school dismissals and social distancing in other settings (e.g., postponement or cancellation of mass gatherings and telework and remote-meeting options in workplaces). These measures can be disruptive and might have societal and economic impact on individual persons and communities ( 6 ). However, studies have shown that early layered implementation of these interventions can reduce the community spread and impact of infectious pathogens such as pandemic influenza, even when specific pharmaceutical treatments and vaccines are not available ( 7 , 8 ). These measures might be critical to avert widespread COVID-19 transmission in U.S. communities ( 2 , 6 ). Mitigation measures implemented in China have included the closing of major transport hubs and preventing exit from certain cities with widespread transmission, cancellation of Chinese New Year celebrations, and prohibition of attendance at school and work ( 5 ). However, the impact of these measures in China has not yet been evaluated. In the United States, the National Institutes of Health (NIH) and their collaborators are working on development of candidate vaccines and therapeutics for COVID-19. In China, multiple clinical trials of investigational therapeutics have been implemented, including two clinical trials of remdesivir, an investigational antiviral drug. §§ An NIH randomized controlled clinical trial of investigational therapeutics for hospitalized COVID-19 patients in the United States was approved by the Food and Drug Administration; the first investigational therapeutic to be studied is remdesivir. ¶¶ In the absence of a vaccine or therapeutic, community mitigation measures are the primary method to respond to widespread transmission and supportive care is the current medical treatment. COVID-19 symptoms are similar to those of influenza (e.g., fever, cough, and shortness of breath), and the current outbreak is occurring during a time of year when respiratory illnesses from influenza and other viruses, including other coronaviruses that cause the “common cold,” are highly prevalent. To prevent influenza and possible unnecessary evaluation for COVID-19, all persons aged ≥6 months should receive an annual influenza vaccine; vaccination is still available and effective in helping to prevent influenza ( 9 ). To decrease risk for respiratory disease, persons can practice recommended preventive measures.*** Persons ill with symptoms of COVID-19 who have had contact with a person with COVID-19 or recent travel to countries with apparent community spread ††† should communicate with their health care provider. Before seeking medical care, they should consult with their provider to make arrangements to prevent possible transmission in the health care setting. In a medical emergency, they should inform emergency medical personnel about possible COVID-19 exposure. Areas for additional COVID-19 investigation include 1) further clarifying the incubation period and duration of virus shedding, which have implications for duration of quarantine and other mitigation measures; 2) studying the relative importance of various modes of transmission, including the role of droplets, aerosols, and fomites; understanding these transmission modes has major implications for infection control and prevention, including the use of personal protective equipment; 3) determining the severity and case-fatality rate of COVD-19 among cases in the U.S. health care system, as well as more fully describing the spectrum of illness and risk factors for infection and severe disease; 4) determining the role of asymptomatic infection in ongoing transmission; and 5) assessing the immunologic response to infection to aid in the development of vaccines and therapeutics. Public health authorities are monitoring the situation closely. As more is learned about this novel virus and this outbreak, CDC will rapidly incorporate new knowledge into guidance for action. Summary What is already known about this topic? An outbreak of coronavirus disease 2019 (COVID-19) has spread throughout China and to 31 other countries and territories, including the United States. What is added by this report? Fourteen cases have been diagnosed in the United States, in addition to 39 cases among repatriated persons from high-risk settings, for a current total of 53 cases within the United States. The U.S. government and public health partners are implementing aggressive measures to slow and contain transmission of COVID-19 in the United States. What are the implications for public health practice? Interim guidance is available at https://www.cdc.gov/coronavirus/index.html. As more is learned about this virus and the outbreak, CDC will rapidly incorporate new knowledge into guidance for action.

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          Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study

          Summary Background In December, 2019, a pneumonia associated with the 2019 novel coronavirus (2019-nCoV) emerged in Wuhan, China. We aimed to further clarify the epidemiological and clinical characteristics of 2019-nCoV pneumonia. Methods In this retrospective, single-centre study, we included all confirmed cases of 2019-nCoV in Wuhan Jinyintan Hospital from Jan 1 to Jan 20, 2020. Cases were confirmed by real-time RT-PCR and were analysed for epidemiological, demographic, clinical, and radiological features and laboratory data. Outcomes were followed up until Jan 25, 2020. Findings Of the 99 patients with 2019-nCoV pneumonia, 49 (49%) had a history of exposure to the Huanan seafood market. The average age of the patients was 55·5 years (SD 13·1), including 67 men and 32 women. 2019-nCoV was detected in all patients by real-time RT-PCR. 50 (51%) patients had chronic diseases. Patients had clinical manifestations of fever (82 [83%] patients), cough (81 [82%] patients), shortness of breath (31 [31%] patients), muscle ache (11 [11%] patients), confusion (nine [9%] patients), headache (eight [8%] patients), sore throat (five [5%] patients), rhinorrhoea (four [4%] patients), chest pain (two [2%] patients), diarrhoea (two [2%] patients), and nausea and vomiting (one [1%] patient). According to imaging examination, 74 (75%) patients showed bilateral pneumonia, 14 (14%) patients showed multiple mottling and ground-glass opacity, and one (1%) patient had pneumothorax. 17 (17%) patients developed acute respiratory distress syndrome and, among them, 11 (11%) patients worsened in a short period of time and died of multiple organ failure. Interpretation The 2019-nCoV infection was of clustering onset, is more likely to affect older males with comorbidities, and can result in severe and even fatal respiratory diseases such as acute respiratory distress syndrome. In general, characteristics of patients who died were in line with the MuLBSTA score, an early warning model for predicting mortality in viral pneumonia. Further investigation is needed to explore the applicability of the MuLBSTA score in predicting the risk of mortality in 2019-nCoV infection. Funding National Key R&D Program of China.
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            Novel Framework for Assessing Epidemiologic Effects of Influenza Epidemics and Pandemics

            Pandemic influenza results from the emergence of a new influenza A virus to which the population possesses little or no immunity ( 1 ). Past pandemic influenza viruses have spread rapidly worldwide, affecting persons of all ages and causing substantial illness and death. Influenza can result in a wide spectrum of clinical outcomes in infected persons, including asymptomatic infection, medically and non–medically attended respiratory illness, hospitalization, or death. The likelihood of these outcomes is variable and depends on many factors, including the age of the patient, the presence of underlying medical conditions, and characteristics of the virus itself ( 2 ). The overall number of illnesses and deaths from influenza in the population may be primarily attributable to a combination of both the clinical severity of illness in infected persons and the transmissibility of the infection in the population. Figure 1 shows the increasing expected number of deaths in the US population as both the cumulative incidence of influenza in the population and the case-fatality ratio (CFR) increase. Figure 1 Estimates of influenza deaths in the 2010 United States population (308,745,538 persons) across varying values of case-fatality ratio and the cumulative incidence of infection in the population. Selected estimated numbers of deaths are indicated with a black line, across each relevant combination of case-fatality ratio and cumulative incidence. In addition, the background color transitions from blue to yellow to red as the estimated absolute number of deaths increases. Because the risk for severe outcomes and differences in the rates of transmission of the virus can vary, the effects on the population observed during pandemics have ranged from those similar to severe seasonal influenza epidemics to those experienced during the 1918 influenza pandemic. Depending on the overall population effects, a pandemic could overwhelm the capacities of public health and health care systems or result in societal disruption because of school or workplace absenteeism, which could affect critical infrastructure ( 1 , 3 ). Historically, assessment of influenza pandemic effects has been characterized by using an estimate of the overall CFR ( 4 ). Although this approach provided guidance for planning and projections of the expected number of deaths from pandemic influenza in the population, using that ratio alone presents several challenges. First, deaths from influenza may occur weeks after illness begins and can also be subject to reporting bias, delaying the ability of public health and government leaders to quickly issue recommendations for evidence-based public health interventions if they lack an accurate estimate of CFR. Second, a single overall CFR does not fully account for the varying effects a seasonal epidemic or pandemic could have on vulnerable population subgroups, which could include children or the elderly, those with chronic conditions, or certain racial and ethnic minorities. Finally, CFR does not address other societal effects, such as absenteeism or the demand on health care services from excess outpatient visits and hospitalizations, that could result from increased transmission. Because of these limitations, relying on CFR as a single measure of the effects on a population may make an assessment difficult if such data are not yet available early in a pandemic or misleading if the available data are not well characterized and the biases are not well understood. The ability to synthesize epidemiologic data collected early during a pandemic to characterize its anticipated public health effects is of vital importance to public health officials in the United States and worldwide. Here we provide a conceptual framework with which to characterize the expected effects of a pandemic in the context of past experience with influenza epidemics and pandemics in the United States. We examined published data from past influenza seasons and pandemics to determine the range of effects of influenza in the United States. The framework provides a basic structure by which to synthesize epidemiologic data and on which preparedness plans can be developed to guide and communicate the pandemic influenza response. Methods We developed the assessment framework using a 4-step process. The steps included were the following: 1) identify and evaluate available measures of influenza transmissibility and severity, 2) create a standard scale for selected measures, 3) summarize and scale available measures, and 4) provide historical context. Step 1: Identify and Evaluate Measures of Transmissibility and Severity We first identified epidemiologic measures that may be indicators of either the transmissibility of a novel influenza virus or the clinical severity in infected persons. The identification of relevant measures within these categories was based on an extensive review of historical seasonal and pandemic influenza literature, including published articles and reports of surveillance data collected from the 1918 pandemic forward. Three criteria were used to evaluate the identified measures: 1) the availability and quality of data related to the measures during the early stages of past influenza pandemics and seasonal influenza epidemics; 2) the presence of enough variation in the measure to produce a biologically plausible and measurable scale; and 3) the epidemiologic strengths and limitations of the measure (Technical Appendix). Step 2: Scaling Measures of Transmissibility and Severity From the list of measures identified in step 1, we abstracted data from the literature review on the measures as reported during previous influenza seasons and pandemics. To create a comparable scale across the various measures of transmissibility and clinical severity, we first identified the range of values that had been observed historically for each measure. The data for each measure were then categorized into a uniform scale that was consistent across indicators of transmissibility and across indicators of clinical severity. Because the availability and quality of epidemiologic information will increase throughout the course of a pandemic, we divided the assessment process into 2 assessment frameworks: 1) an “initial assessment” when data are sparse or very uncertain, and 2) a “refined assessment” when data are more available and more certain. A uniform scale of the transmissibility and clinical severity indicators was developed for each framework. When transmission of a novel influenza virus is identified, early epidemiologic measures provide a broad initial assessment, albeit with a high level of uncertainty, and were categorized by using a broad dichotomous scale. The assessment framework would become more refined as additional epidemiologic and clinical information are gathered and the biases in the earliest measures are better characterized. During this period, a similar general framework would incorporate a finer scale, allowing for more discrete separation of seasonal epidemics and pandemics. Step 3: Summarize and Score Available Measures During the initial assessment, a combination of the dichotomous scale for indicators of transmissibility and the dichotomous scale for indicators of severity results in a framework with 4 profiles (A, B, C, D) (Figure 2). An initial assessment can be made as soon as data on some measures become available and would continue to be reviewed and revised as the data warrant. As early data become available, issues of data quality are also essential to consider; we include a list of such considerations in the Technical Appendix. Once more robust data are available, the assessment could transition to the more detailed scale of the refined assessment framework, with scaled values of severity and transmissibility plotted along an x-axis and y-axis, respectively (Figure 3). Because the effects of an influenza pandemic may vary between age groups, the refined assessment could also be conducted with age-stratified data on indicators of transmissibility and clinical severity and then plotted by using the same scale and framework (Figure 4). Figure 2 Framework for the initial assessment of the effects of an influenza pandemic. Figure 3 Framework for the refined assessment of the effects of an influenza pandemic, with scaled examples of past pandemics and past influenza seasons. Color scheme included to represent corresponding estimates of influenza deaths in the 2010 US population as shown in Figure 1. Figure 4 Framework for the refined assessment of the effects of an influenza pandemic, stratified by age group with scaled examples from the 2009 pandemic. Color scheme included to represent corresponding estimates of influenza deaths in the 2010 US population as shown in Figure 1. Step 4: Provide Historical Context For the refined assessment, we scaled and plotted data from obtained from our literature riew for 4 pandemics (2009, 1968, 1957, 1918) and 3 nonpandemic influenza seasons that ranged in transmissibility and severity (1978–79, 2006–07, and 2007–08) (Technical Appendix). When multiple measures for transmissibility or severity were present, we used the median score across all available measures. Age-stratified data from the 2009 influenza A (H1N1) pandemic were also similarly scaled and plotted by using the age categories 65 years. Results Initial Assessment Early in a pandemic, the spread of a novel virus is likely to be restricted to a particular geographic area, mostly in focal clusters of infections, and epidemiologic data are limited. To reflect the uncertainty in early data, we divided each measure of transmissibility and severity for the initial assessment framework into a dichotomous scale corresponding to the low-moderate and moderate-high ends of the range of values from the literature review. Scaled values for the initial assessment are shown in Table 1. Table 1 Scaled measures of transmissibility and clinical severity for the initial assessment of pandemic influenza effects Parameter no. and description Scale Low-moderate Moderate-high Transmissibility 1. Secondary attack rate, household, % 20 2. Attack rate, school or university, % 30 3. Attack rate, workplace or community, % 20 4. R0: basic reproductive no. 1.0–1.7 >1.8 5. Underlying population immunity Some underlying population immunity present No underlying population immunity present 6. Emergency department or other outpatient visits for influenza-like illness, % 1 2. Upper boundary of case-hospitalization ratio, % 10 3. Ratio, deaths: hospitalizations, % 10 4. Virologic characterization Genetic markers for virulence absent Genetic markers for virulence present 5. Animal models Less virulent or similar to seasonal influenza More virulent than seasonal influenza We recognized that early measures are likely to have substantial biases. Early measures of the transmissibility of the virus are likely to come from larger recognized outbreaks, which may lead to higher estimates than would eventually occur in the whole population. Likewise, early indicators of severity may be overestimated if severe illnesses are more likely to be recognized, as was seen worldwide early in the 2009 influenza A (H1N1) pandemic ( 5 , 6 ). For example, reports to the Centers for Disease Control and Prevention (Atlanta, GA, USA) of confirmed cases in the first few weeks of the 2009 pandemic indicated a crude CFR of 0.3% ( 7 ), ≈10-fold higher than it was estimated to be following adjustment for underdetection ( 5 , 8 ). To account for this bias in early measurements, we set the midpoint of the CFR in the initial assessment 10× higher than the midpoint in the refined assessment. Early measures of transmissibility were then scaled along a y-axis, and early measures of clinical severity were scaled along an x-axis. From the combination of these 2 dichotomous scales, the initial framework results in 4 quadrants (Figure 2). In quadrant A, for example, available indicators appear similar to the range seen in annual seasonal epidemics. For quadrant B, although clinical severity is in the range of that seen in seasonal epidemics, the transmissibility is greater and thus overall rates of severe outcomes may be greater. Conversely, in quadrant C, transmissibility is similar to that of seasonal epidemics, but severity is expected to be higher, again leading to increased expected rates of severe outcomes, but for a different reason. Finally, in quadrant D, both indicators are greater than expected during annual seasonal epidemics. Consequently, recommended guidance and interventions during the pandemic response may be different between the quadrants. Refined Assessment Although the assessment would be updated routinely as new data become available, an increase in the amount and quality of data will allow results to be presented in a more precise, refined assessment. For this framework, the range for each measure of transmissibility was divided into a 5-point scale while the range for each measure of clinical severity, which covered a broader range of values, was divided along a 7-point scale. To illustrate this assessment framework, we selected 5 measures of transmissibility and 3 measures of severity to scale on the basis of information obtained in our literature review. Detailed discussions of the measures and their strengths and limitations are in the Technical Appendix. Table 2 displays the ordinal scales for the measures of transmissibility and clinical severity that we developed for the refined assessment. For example, a cumulative symptomatic attack rate of 12% would be classified as a 2 on the scale, whereas a cumulative symptomatic attack rate of 28% would be a 5 on the scale. Likewise, a CFR of 0.01% would be a 1 on the clinical severity scale, whereas a CFR of 1.2% would be a 7. Each measure followed this approach with a scale of 1, representing the lowest observed values for that parameter, with values increasing as the scale increases. Table 2 Scaled measures of transmissibility and clinical severity for the refined assessment of pandemic influenza effects Parameter no. and description Scale 1 2 3 4 5 6 7 Transmissibility 1. Symptomatic attack rate, community, % 25 2. Symptomatic attack rate, school, % 36 3. Symptomatic attack rate, workplace, % 25 4. Household secondary attack rate, symptomatic, % 21 5. R0: basic reproductive no. 1.8 6. Peak % outpatient visits for influenza-like illness 1–3 4–6 7–9 10–12 >13 Clinical severity 1. Case-fatality ratio, % 1 2. Case-hospitalization ratio, % 7 3. Ratio, deaths: hospitalization, % 18 Using available measures of transmissibility and clinical severity and the scale in Table 2, we plotted the coordinates for several sample years on the refined assessment framework. For example, using the 2009 pandemic (Table 3), available measures of clinical severity included the symptomatic CFR, the symptomatic case-hospitalization ratio, and the ratio of deaths to hospitalizations ( 5 , 8 ). Each of these measurements was a 2 on the ordinal scale of clinical severity. Available measures of transmissibility from 2009 included a household secondary attack rate ( 9 – 11 ), an estimated population clinical attack rate ( 12 ), an estimated R0 ( 13 ), and a peak percent of visits for influenza-like illness from national surveillance ( 14 ). Each of these measurements was a 3 on the scale of transmissibility. This is illustrated at the coordinate ( 2 , 3 ) in Figure 3. We likewise characterized data abstracted from past pandemics and selected previous seasons and also plotted them as shown in Figure 3. Further details are included in the Technical Appendix. Table 3 Indicators of severity and transmissibility from the 2009 influenza (H1N1) pandemic and the corresponding assessment scale Parameter Value Score Clinical severity Symptomatic case-fatality ratio, % 0.02 2 Symptomatic case-hospitalization ratio, % 0.05 2 Ratio, deaths: hospitalization, % 4.7 2 Overall 2 Transmissibility Household secondary attack rate, 
 symptomatic, % 13 3 Symptomatic attack rate, community, % 20 3 Peak % visits for influenza-like illness 7 3 R0: basic reproductive no. 1.4 3 Overall 3 In addition, we abstracted and scaled data from the 2009 pandemic by age group. These values were plotted in Figure 4, with the dashed box representing the overall assessment of the 2009 pandemic. As shown, the available data indicated that persons 65 years of age, however, had little illness (an overall symptomatic attack rate of 15% [ 12 ], 2 on the transmission scale), but more of those who became ill died (a CFR of 0.18% [ 5 , 8 ], 4 on the clinical severity scale). Persons 18–64 years of age had values that were similar to those of the overall assessment. Discussion A new framework to assess pandemic effects was developed to systematically assess the potential population effects of an influenza pandemic by characterizing data on both transmissibility and clinical severity and providing historical context from past pandemics and influenza seasons. We divided the framework into 2 periods. In the initial assessment, during the early stages of a pandemic, few epidemiologic data may be available and early indicators can be variable. These indications were thus categorized by using a broad dichotomous scale. In the refined assessment, as increased data become available later in a pandemic, the ranges of transmissibility and severity measures were more finely categorized. Rather than rely only on a single measure, such as the CFR, to assess the potential effects of a pandemic, which may be misleading if those data are unavailable or not representative early in the pandemic, we incorporated several epidemiologic measures into the framework, although the CFR remains a valuable measure of clinical severity. With the creation of a standard scale that includes multiple epidemiologic measures, a variety of data may be incorporated to help synthesize these different measures into an overall indicator of transmissibility and clinical severity. The visualization of epidemiologic data in the framework provides epidemiologists, public health officials, and policy makers with an evidence-based assessment of influenza transmissibility and clinical severity in the context of previous influenza seasons and pandemics. Although the 3 selected influenza seasons are positioned in a cluster in the lower left of Figure 3, discernible differences exist between the seasons. During the 2006–07 season, subtype A/H1N1 viruses predominated ( 15 ), producing what has been generally regarded as a milder season in the United States; this season received the lowest score for both transmissibility and clinical severity. Conversely, during the 2007–08 season, subtype A/H3N2 viruses predominated ( 16 ) to produce what has been generally regarded as a more severe season. This season is positioned toward the center of the graph, which indicates greater transmissibility and clinical severity than was seen in 2006–07. The 3 modern pandemics (2009, 1968, and 1957) are clustered in the upper center of the graph, indicating that these pandemics had higher transmissibility but that overall clinical severity was either at or moderately above the level observed during some recent influenza seasons. In contrast, the 1918 pandemic was positioned at the upper right corner of the graph, indicating a very transmissible and clinically severe pandemic with extensive effects in the population. An evidence-based assessment of pandemic effects is essential to inform decision makers early in a pandemic and enable them to develop and communicate preventive recommendations to reduce illness and death. The context provided by the assessment of transmissibility and severity can inform the selection of pharmacologic and nonpharmacologic interventions that may be appropriate to mitigate the anticipated effects of a pandemic. For example, although the early initial assessment was categorized into only 4 quadrants, this broad early assessment can help organize available information to facilitate early decision-making that may need to be initiated when data are still limited. When clinical severity is high (quadrants C/D), measures may be initiated to provide early treatment to all who are ill and to reduce spread to limit severe disease outcomes and demand on health systems. If clinical severity appears to be similar to seasonal epidemics, but incidence is high (quadrant B), measures may be taken to reduce transmission and prepare for the possibility of disruption in schools and workplaces due to absenteeism. As more data are collected, the assessment transitions into a more detailed refined assessment, and a better characterization of the risks of transmissibility and clinical severity. Subsequently, recommendations and communications may be refined to better reflect the potential effects of the evolving pandemic. Work is ongoing at the Centers for Disease Control and Prevention to use the assessment framework to select different combinations of transmissibility and clinical severity and develop prepandemic guidance on the basis of the potential effects in the population. Although this framework provided an assessment of the potential population effects from an influenza pandemic, it should not be used in isolation of other epidemiologic data. As this study illustrated, the assessment may be stratified to incorporate data on transmissibility and severity by age group or other risk factors to assess how the expected effects might vary in and across these groups. In addition, decision makers should consider the potential effects in relation to the time at which the pandemic emerges and the particular course of the epidemic in an area (i.e., early vs. approaching peak activity). For example, although the United States experienced a peak of pandemic activity in the late spring of 2009, for most of the country that wave ultimately accounted for only ≈5%–8% of the total estimated burden of influenza during the first year of the pandemic ( 5 , 12 ). Decision makers should also consider additional factors that are relevant to their individual communities, regions, and states when formulating guidance for interventions based on the epidemiologic impact assessment. These considerations include factors such as access to adequate health care and public health interventions among the affected population, the demographic make-up, the presence of vulnerable populations, or the population density. Our assessment is subject to some limitations. We conducted a literature review of published data on measures of transmissibility and clinical severity from past influenza seasons and pandemics. Some data were sparse or contradictory, making it difficult to fully understand the variability within measures and the comparability between measures. However, building the framework around a standard scale provides flexibility to refine how measures are categorized as additional data become available and allows for other measures to also be incorporated into the scale. This lack of data underscores the need for ongoing study of the epidemiology of annual epidemics of influenza to improve our ability to accurately characterize the variability in the transmissibility and severity of influenza. An increased understanding of the effects of seasonal influenza will help the public health community prepare for the potential effects of a novel influenza virus. In addition, there will be biases and limitations in the measurement or availability of epidemiologic data to incorporate in the framework. The Technical Appendix describes an evaluation of several epidemiologic measures and available data sources. We attempted to account for some of the known biases by adjusting the scales used in the initial assessment on the basis of the most recent experience of the 2009 pandemic. However, changes in care-seeking behavior or testing practices may require readjusting the scale to more accurately reflect future trends. It is also possible that severity could be underestimated initially because of the delay from illness to death, which we did not directly account for ( 17 ). In the case of influenza, however, this underestimation may have less bearing than the substantial underrecognition of community transmission ( 6 ). Continued refinement of the methods by which we collect and analyze data annually on influenza will improve our ability to have accurate and reliable data during a pandemic. A key challenge in assessing the effects of an influenza pandemic is that many cases of influenza are mild, even in the most severe pandemics, and not all persons will seek medical care or be tested for influenza. This leads to an underestimation of the incidence by missing persons who do not seek medical care and biases estimates of severity by disproportionately detecting more severe cases. Developing novel methods to better characterize the community effects of influenza will be vital to define a more accurate case denominator. In addition, strengthening systematic surveillance methods and better characterizing existing systems will also help address some of the biases in the detection of influenza and the estimation of key epidemiologic parameters. Although we used data from the United States, the framework provides a basic structure to synthesize epidemiologic data that may be useful in other settings as well. The measures used to characterize epidemics and pandemics of influenza have both strengths and limitations; thus, we developed a the framework that is flexible and can be adapted over time to incorporate or refine measures as more data become available or better characterized. Further evaluation of the framework will be needed to determine whether it will be used as a formal policy for pandemic planning and response. This standardized approach informs the assessment of pandemic impact by organizing available epidemiologic information using a set of key parameters to prioritize data collection and facilitate decision making. Technical Appendix Description of process used to evaluate measures of influenza transmissibility and severity characterized historically in the literature.  Parts A and B review measures that could be used to characterize novel influenza viruses and pandemics and include a detailed discussion of their strengths and limitations.  Part C outlines several data quality issues that should be considered in the inclusion of data in the assessment framework.  Finally, Part D provides additional detail on the data abstracted from the literature on past pandemics and selected seasons that were used to scale examples provided in the manuscript.
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              Interim Estimates of 2019–20 Seasonal Influenza Vaccine Effectiveness — United States, February 2020

              During the 2019–20 influenza season, influenza-like illness (ILI)* activity first exceeded the national baseline during the week ending November 9, 2019, signaling the earliest start to the influenza season since the 2009 influenza A(H1N1) pandemic. Activity remains elevated as of mid-February 2020. In the United States, annual vaccination against seasonal influenza is recommended for all persons aged ≥6 months ( 1 ). During each influenza season, CDC estimates seasonal influenza vaccine effectiveness in preventing laboratory-confirmed influenza associated with medically attended acute respiratory illness (ARI). This interim report used data from 4,112 children and adults enrolled in the U.S. Influenza Vaccine Effectiveness Network (U.S. Flu VE Network) during October 23, 2019–January 25, 2020. Overall, vaccine effectiveness (VE) against any influenza virus associated with medically attended ARI was 45% (95% confidence interval [CI] = 36%–53%). VE was estimated to be 50% (95% CI = 39%–59%) against influenza B/Victoria viruses and 37% (95% CI = 19%–52%) against influenza A(H1N1)pdm09, indicating that vaccine has significantly reduced medical visits associated with influenza so far this season. Notably, vaccination provided substantial protection (VE = 55%; 95% CI = 42%–65%) among children and adolescents aged 6 months–17 years. Interim VE estimates are consistent with those from previous seasons, ranging from 40%–60% when influenza vaccines were antigenically matched to circulating viruses. CDC recommends that health care providers continue to administer influenza vaccine to persons aged ≥6 months because influenza activity is ongoing, and the vaccine can still prevent illness, hospitalization, and death associated with currently circulating influenza viruses as well as other influenza viruses that might circulate later in the season. Methods used by the U.S. Flu VE Network have been published previously ( 2 ). At five study sites (Michigan, Pennsylvania, Texas, Washington, and Wisconsin), patients aged ≥6 months seeking outpatient medical care for an ARI with cough within 7 days of illness onset were enrolled once local influenza circulation was identified. † Enrollment eligibility criteria included 1) age ≥6 months on September 1, 2019 (i.e., vaccine-eligible); 2) ARI with cough, with onset ≤7 days earlier; and 3) no treatment with influenza antiviral medication (e.g., oseltamivir or baloxavir) during this illness. Consenting participants or their proxies were interviewed to collect demographic data, information on general and current health status and symptoms, and 2019–20 influenza vaccination status. Nasal and oropharyngeal swabs (nasal swabs alone for children aged 99%) belonged to the B/Victoria lineage, and three (<1%) belonged to the B/Yamagata lineage. Among 335 subtyped influenza A viruses, 326 (97%) were A(H1N1)pdm09 viruses, and only 11 (3%) were A(H3N2) viruses. The proportion of patients with influenza differed among study sites, age groups, racial/ethnic groups, self-rated health status, and days from illness onset to enrollment. The percentage of ARI patients who were vaccinated ranged from 38% to 61% among study sites and differed by study site, sex, age group, race/ethnicity, self-rated health status, and days from illness onset to enrollment. TABLE 1 Influenza real-time reverse transcription–polymerase chain reaction test results and seasonal vaccination status among patients with medically attended acute respiratory illness (N = 4,112), by selected characteristics — U.S. Influenza Vaccine Effectiveness Network, October 23, 2019—January 25, 2020 Characteristic Test result status Total no. of patients Vaccinated 
no. (%)† P-value* Influenza-positive
no. (%) Influenza-negative
no. (%) P-value* Overall 1,060 (26) 3,052 (74) N/A 4,112 2,072 (50) N/A Study site Michigan 94 (25) 280 (75) 0.001 374 226 (60) <0.001 Pennsylvania 222 (32) 466 (68) 688 346 (50) Texas 303 (25) 916 (75) 1,219 469 (38) Washington 236 (23) 787 (77) 1,023 620 (61) Wisconsin 205 (25) 603 (75) 808 411 (51) Sex Male 448 (27) 1,198 (73) 0.08 1,646 789 (48) 0.01 Female 612 (25) 1,854 (75) 2,466 1,283 (52) Age group 6 mos–8 yrs 263 (29) 652 (71) <0.001 915 470 (51) <0.001 9–17 yrs 199 (41) 282 (59) 481 164 (34) 18–49 yrs 413 (28) 1,084 (72) 1,497 595 (40) 50–64 yrs 113 (18) 532 (82) 645 372 (58) ≥65 yrs 72 (13) 502 (87) 574 471 (82) Race/Ethnicity§ White 691 (24) 2,169 (76) 0.002 2,860 1,522 (53) <0.001 Black 120 (32) 260 (68) 380 134 (35) Other race 111 (28) 291 (72) 402 227 (56) Hispanic 137 (30) 325 (70) 462 186 (40) Self-rated health status¶ Fair or poor 55 (18) 248 (82) <0.001 303 182 (60) <0.001 Good 231 (21) 866 (79) 1,097 576 (53) Very good 393 (26) 1,141 (74) 1,534 761 (50) Excellent 380 (32) 794 (68) 1,174 549 (47) Illness onset to enrollment (days) <3 492 (35) 900 (65) <0.001 1,392 653 (47) <0.001 3–4 390 (26) 1,099 (74) 1,489 713 (48) 5–7 178 (14) 1,053 (86) 1,231 706 (57) Influenza test result Negative N/A 3,052 (74) N/A 3,052 1,682 (55) N/A Influenza B positive** 691 (17) N/A 691 232 (34) B/Yamagata 3 (<1) N/A 3 3 (100) B/Victoria 670 (93) N/A 670 221 (33) B lineage undetermined 18 (7) N/A 18 8 (44) Influenza A positive** 374 (9) N/A 374 161 (43) A (H1N1)pdm09 326 (63) N/A 326 138 (42) A (H3N2) 11 (3) N/A 11 7 (64) A subtype undetermined 39 (34) N/A 39 16 (41) Abbreviation: N/A = not applicable. * The chi-squared statistic was used to assess differences between the numbers of persons with influenza-negative and influenza-positive test results, in the distribution of enrolled patient and illness characteristics, and in differences between groups in the percentage vaccinated. † Defined as having received ≥1 dose of influenza vaccine ≥14 days before illness onset. A total of 104 participants who received the vaccine ≤13 days before illness onset were excluded from the study sample. § Patients were categorized into one of four mutually exclusive racial/ethnic populations: white, black, other race, and Hispanic. Persons identifying as Hispanic might have been of any race. Persons identifying as white, black, or other race were non-Hispanic. Race/ethnicity was missing for eight patients. ¶ General self-rated health status was missing for four patients. ** Five patients had coinfection with influenza A and influenza B, making the sum 1,065, or five more than the total number of influenza-positive patients. Two patients had coinfection with influenza A(H1N1)pdm09 and A(H3N2). Among influenza-positive participants, 37% had received the 2019–20 seasonal influenza vaccine, compared with 55% of influenza-negative participants (Table 2). Overall, the adjusted VE was 45% against influenza A and B virus types combined, 50% against influenza B/Victoria, and 37% against A(H1N1)pdm09. VE was higher among children and adolescents aged 6 months–17 years and lower among adults aged 18–49 years, especially against A(H1N1)pdm09 (VE = 5%; 95% CI = -45% to 37%). TABLE 2 Number and percentage of outpatients with acute respiratory illness and cough (N = 4,112) receiving 2019–20 seasonal influenza vaccine, by influenza real-time reverse transcription–polymerase chain reaction (RT-PCR) test result status, age group, and vaccine effectiveness* against all influenza A and B, B/Victoria and A(H1N1)pdm09 — U.S. Influenza Vaccine Effectiveness Network, October 23, 2019–January 25, 2020 Influenza type/Age group Influenza-positive Influenza-negative Vaccine effectiveness Total Vaccinated
no. (%) Total Vaccinated
no. (%) Unadjusted
% (95% CI) Adjusted†
% (95% CI) Influenza A and B Overall 1,060 390 (37) 3,052 1,682 (55) 53 (45 to 59) 45 (36 to 53) Age group 6 mos–17 yrs 462 142 (31) 934 492 (53) 60 (50 to 69) 55 (42 to 65) 18–49 yrs 413 143 (35) 1,084 452 (42) 26 (6 to 42) 25 (3 to 41) ≥50 yrs 185 105 (57) 1,034 738 (71) 47 (27 to 62) 43 (19 to 60) Influenza B/Victoria Overall 634 211 (33) 2,968 1,641 (55) 60 (52 to 66) 50 (39 to 59) Age group 6 mos–17 yrs 353 104 (29) 934 492 (53) 62 (51 to 71) 56 (42 to 67) ≥18 yrs 317 117 (37) 2,118 1,190 (56) 54 (42 to 64) 32 (11 to 48) Influenza A(H1N1)pdm09 Overall 326 138 (42) 3,052 1,682 (55) 40 (25 to 53) 37 (19 to 52) Age group 6 mos–17 yrs 98 35 (36) 934 492 (53) 50 (23 to 68) 51 (22 to 69) 18–49 yrs 125 48 (38) 1,084 452 (42) 13 (−27 to 40) 5 (−45 to 37) ≥50 yrs 103 55 (53) 1,034 738 (71) 54 (31 to 69) 50 (20 to 68) * Vaccine effectiveness was estimated as 100% x (1 − odds ratio [ratio of odds of being vaccinated among outpatients with CDC’s real-time RT-PCR influenza-positive test results to the odds of being vaccinated among outpatients with influenza-negative test results]); odds ratios were estimated using logistic regression. † Adjusted for study site, age group, sex, race/ethnicity, self-rated general health, number of days from illness onset to enrollment, and month of illness using logistic regression. As of January 25, 2020, CDC had genetically characterized 177 influenza B/Victoria viruses from U.S. Flu VE Network participants; 172 (97%) belonged to genetic subclade V1A.3, a different subclade from the V1A.1 subclade that includes the 2019–20 B/Victoria vaccine reference strain (B/Colorado/06/2017), and five (3%) belonged to V1A.1. All of the 32 genetically characterized A(H1N1)pdm09 viruses were from genetic group 6B.1A, which includes the 2019–20 A(H1N1)pdm09 vaccine reference strain (A/Brisbane/02/2018). Discussion The 2019–20 influenza season began early with predominant influenza B/Victoria virus circulation, followed by increasing A(H1N1)pdm09 virus activity, with ongoing detection of both viruses ( 3 ). Through the week ending February 8, 2020, influenza activity remained elevated in most parts of the country (https://www.cdc.gov/flu/weekly). Markers of severe illness, including laboratory-confirmed influenza-associated hospitalization rates among children and adolescents aged <18 years and young adults aged 18–49 years, are higher than at this time in recent seasons, including the 2017–18 season. To date for this season, 92 influenza-associated deaths have been reported in children and adolescents aged <18 years; other than the 2009 pandemic, this is the largest number reported for this time of the season since reporting began for the 2004–05 influenza season (https://www.cdc.gov/flu/weekly). These interim VE estimates indicating a 45% reduction in influenza illness associated with a medical visit so far this season are particularly important in the context of the substantial prevalence of influenza in the United States: during the previous decade, influenza caused an estimated 4.3–21 million doctor visits, 140,000–810,000 hospitalizations, and 12,000–61,000 deaths each year. †† Among U.S. Flu VE Network participants, influenza virus infections accounted for approximately 25% of medically attended visits for ARI, demonstrating the considerable contribution of influenza virus infections to medically attended outpatient visits for ILI this season. Both influenza A and B viruses can cause severe illness, including hospitalizations and deaths. Some studies have suggested that influenza B virus infections might also result in more severe illness among children ( 4 , 5 ). Interim VE estimates indicate that the 2019–20 influenza vaccine protects against the predominant B/Victoria viruses from subclade V1A.3 and are consistent with VE estimates against influenza B/Victoria (range = 49%–56%) during seasons when the B/Victoria component of the vaccine was well matched to circulating viruses. §§ Influenza A(H1N1)pdm09 circulation increased in late December 2019; as of January 31, 2020, all A(H1N1)pdm09 viruses antigenically characterized at CDC were similar to the cell-propagated vaccine reference virus for the A(H1N1)pdm09 component of the 2019–20 Northern Hemisphere vaccine. Interim VE estimates against influenza A(H1N1)pdm09 viruses among children and older adults are consistent with average VE for influenza A(H1N1)pdm09 viruses reported previously ( 6 ). Among adults aged 18–49 years, the interim VE estimate against influenza A(H1N1)pdm09 was low and not statistically significant. Additional enrollment during the season while A(H1N1)pdm09 viruses circulate will determine whether VE against A(H1N1)pdm09 in this age group is lower than during previous seasons and will help evaluate potential contributing factors to lower than expected effectiveness. During the five previous influenza seasons, the number of weeks that ILI activity was above baseline ranged from 11 to 20 weeks, with an average of 18 weeks ( 7 ). At 21 weeks, the 2018–19 influenza season was prolonged, demonstrating that influenza activity can continue beyond the winter months. CDC continues to recommend influenza vaccination while influenza viruses are circulating. Vaccination can protect against infection with influenza viruses that are currently circulating and those that might circulate later in the season. During the 2018–19 influenza season, in which influenza A(H3N2) and A(H1N1)pdm09 viruses cocirculated, interim VE was estimated to be 29% against illnesses associated with any influenza virus ( 8 ) and vaccination was estimated to prevent 4.4 million illnesses, 2.3 million medical visits, 58,000 hospitalizations, and 3,500 deaths ( 9 ). Current influenza vaccines are providing substantial public health benefits; however, more effective influenza vaccines are needed. Therefore, many U.S. government agencies (including CDC, the National Institutes of Health, the Food and Drug Administration, and the Biomedical Advanced Research and Development Authority) are collaborating to improve influenza vaccines in support of the executive order issued by the White House on September 19, 2019. ¶¶ Influenza antiviral medications remain an important adjunct to influenza vaccination. CDC recommends antiviral treatment for any patient with suspected or confirmed influenza who is hospitalized, has severe or progressive illness, or is at high risk for complications from influenza, including children aged <2 years and adults aged ≥65 years, regardless of vaccination status or results of point-of-care influenza diagnostic testing.*** Antiviral treatment can also be considered for any previously healthy symptomatic outpatient not at high risk for complications, with confirmed or suspected influenza, if treatment can be started within 48 hours of illness onset. The findings in this report are subject to at least four limitations. First, sample sizes were insufficient to estimate overall VE against illnesses associated with A(H3N2) virus infections. End-of-season VE estimates could change as additional patient data become available or if a change in circulating viruses occurs later in the season. Second, vaccination status included self-report at four of five sites, which might result in misclassification of vaccination status for some patients. Third, an observational study design has more potential for confounding and bias than do randomized clinical trials. However, the test-negative design is widely used in VE studies and has been extensively validated, including against findings from randomized trials ( 10 ). Finally, the VE estimates in this report are limited to the prevention of outpatient medical visits rather than more severe illness outcomes, such as hospitalization or death; data from studies measuring VE against more severe outcomes this season will be available at a later date. Annual influenza vaccination is the best strategy for preventing seasonal influenza and influenza-associated complications. This season, influenza B and A(H1N1)pdm09 viruses have cocirculated, and influenza activity remains elevated in most parts of the country. Interim VE estimates indicate that the current season’s influenza vaccine reduces the risk of medical visits associated with influenza, including visits associated with circulating influenza B viruses. Persons aged ≥6 months who have not yet received influenza vaccine during the current season should get vaccinated to protect against influenza. Summary What is already known about this topic? Annual vaccination against seasonal influenza is recommended for all U.S. persons aged ≥6 months. Effectiveness of seasonal influenza vaccine varies by season. What is added by this report? According to data from the U.S. Influenza Vaccine Effectiveness Network on 4,112 children and adults with acute respiratory illness during October 23, 2019–January 25, 2020, the overall estimated effectiveness of seasonal influenza vaccine for preventing medically attended, laboratory-confirmed influenza virus infection was 45%. What are the implications for public health practice? Vaccination remains the best way to protect against influenza and its potentially serious complications. CDC continues to recommend influenza vaccination while influenza viruses are circulating in the community.
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                Author and article information

                Journal
                MMWR Morb Mortal Wkly Rep
                MMWR Morb. Mortal. Wkly. Rep
                WR
                Morbidity and Mortality Weekly Report
                Centers for Disease Control and Prevention
                0149-2195
                1545-861X
                28 February 2020
                28 February 2020
                : 69
                : 8
                : 216-219
                Affiliations
                [1 ]CDC COVID-19 Response Team, CDC.
                Author notes
                Corresponding author: Daniel B. Jernigan, eocevent294@ 123456cdc.gov , 770-488-7100.
                Article
                mm6908e1
                10.15585/mmwr.mm6908e1
                7367075
                32106216
                0db2f056-5d85-4849-bb5d-97fe5e9e3a4d

                All material in the MMWR Series is in the public domain and may be used and reprinted without permission; citation as to source, however, is appreciated.

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