This file contains the provisional percent of total deaths by week for COVID-19, Influenza, and Respiratory Syncytial Virus for deaths occurring among residents in the United States. Provisional data are based on non-final counts of deaths based on the flow of mortality data in National Vital Statistics System.

Monthly Cumulative Number and Percent of Persons Who Received ≥1 Influenza Vaccination Doses, by Flu Season, Age Group, and Jurisdiction

• Influenza vaccination coverage for children and adults is assessed through U.S. jurisdictions’ Immunization Information Systems (IIS) data, submitted from jurisdictions to CDC monthly in aggregate by age group. More information about the IIS can be found at https://www.cdc.gov/vaccines/programs/iis/about.html.

• Influenza vaccination coverage estimate numerators include the number of people receiving at least one dose of influenza vaccine in a given flu season, based on information that state, territorial, and local public health agencies report to CDC. Some jurisdictions’ data may include data submitted by tribes. Estimates include persons who are deceased but received a vaccination during the current season. People receiving doses are attributed to the jurisdiction in which the person resides unless noted otherwise. Quality and completeness of data may vary across jurisdictions. Influenza vaccination coverage denominators are obtained from 2020 U.S. Census Bureau population estimates.

• Monthly estimates shown are cumulative, reflecting all persons vaccinated from July through a given month of that flu season. Cumulative estimates include any historical data reported since the previous submission. National estimates are not presented since not all U.S. jurisdictions are currently reporting their IIS data to CDC. Jurisdictions reporting data to CDC include U.S. states, some localities, and territories.

• Because IIS data contain all vaccinations administered within a jurisdiction rather than a sample, standard errors were not calculated and statistical testing for differences in estimates across years were not performed.

• Laws and policies regarding the submission of vaccination data to an IIS vary by state, which may impact the completeness of vaccination coverage reflected for a jurisdiction. More information on laws and policies are found at https://www.cdc.gov/vaccines/programs/iis/policy-legislation.html.

• Coverage estimates based on IIS data are expected to differ from National Immunization Survey (NIS) estimates for children (https://www.cdc.gov/flu/fluvaxview/dashboard/vaccination-coverage-race.html) and adults (https://www.cdc.gov/flu/fluvaxview/dashboard/vaccination-adult-coverage.html) because NIS estimates are based on a sample that may not be representative after survey weighting and vaccination status is determined by survey respondent rather than vaccine records or administrations, and quality and completeness of IIS data may vary across jurisdictions. In general, NIS estimates tend to overestimate coverage due to overreporting and IIS estimates may underestimate coverage due to incompleteness of data in certain jurisdictions.

This dataset contains the weekly estimated influenza risk level for each ZIP Code in Chicago. Estimates are made during flu season, which goes from MMWR week 40 to week 20 of the following year. The risk level is based on observed level of Influenza-Like Illness (ILI). ILI Activity Level is determined as follows: ILI percentage for each ZIP Code for the week is compared to the mean ILI percentage during the non-influenza months (summer months). Level 1 corresponds to an ILI percentage below the mean, level 2 to an ILI percentage less than one standard deviation (SD) above the mean, level 3 to an ILI percentage more than one, but less than two SDs above mean, and so on, with level 10 corresponding to an ILI percentage more than eight SDs above the mean. For more information on ESSENCE, which compiles the estimates, see https://www.dph.illinois.gov/data-statistics/syndromic-surveillance All data are provisional and subject to change. Information is updated as additional details are received. At any given time, this dataset reflects data currently known to CDPH. Numbers in this dataset may differ from other public sources.

Rank, number of deaths, percentage of deaths, and age-specific mortality rates for the leading causes of death, by age group and sex, 2000 to most recent year.

Chicago residents who are up to date with influenza vaccines by ZIP Code, based on the reported home address and age group of the person vaccinated, as provided by the medical provider in the Illinois Comprehensive Automated Immunization Registry Exchange (I-CARE). “Up to date” refers to individuals aged 6 months and older who have received 1+ doses of influenza vaccine during the current season, defined as the beginning of July (MMWR week 27) through the end of the following June (MMWR week 26). Data Notes: Weekly cumulative totals of people up to date are shown for each combination ZIP Code and age group. Note there are rows where age group is "All ages" so care should be taken when summing rows. Weeks begin on a Sunday and end on a Saturday. Coverage percentages are calculated based on the cumulative number of people in each ZIP Code and age group who are considered up to date as of the week ending date divided by the estimated number of people in that subgroup. Population counts are obtained from the 2020 U.S. Decennial Census. For ZIP Codes mostly outside Chicago, coverage percentages are not calculated because reliable Chicago-only population counts are not available. Actual counts may exceed population estimates and lead to coverage estimates that are greater than 100%, especially in smaller ZIP Codes with smaller populations. Additionally, the medical provider may report a work address or incorrect home address for the person receiving the vaccination, which may lead to over- or underestimation of vaccination coverage by geography. All coverage percentages are capped at 99%. The Chicago Department of Public Health (CDPH) uses the most complete data available to estimate influenza vaccination coverage among Chicagoans, but there are several limitations that impact our estimates. Influenza vaccine administration is not required to be reported in Illinois, except for publicly funded vaccine (e.g., Vaccines for Children, Section 317). Individuals may receive vaccinations that are not recorded in I-CARE, such as those administered in another state, or those administered by a provider that does not submit data to I-CARE, causing underestimation of the number individuals who received an influenza vaccine for the current season. All data are provisional and subject to change. Information is updated as additional details are received and it is, in fact, very common for recent dates to be incomplete and to be updated as time goes on. At any given time, this dataset reflects data currently known to CDPH. Numbers in this dataset may differ from other public sources due to when data are reported and how City of Chicago boundaries are defined. For all datasets related to influenza, see https://data.cityofchicago.org/browse?limitTo=datasets&sortBy=alpha&tags=flu . Data Source: Illinois Comprehensive Automated Immunization Registry Exchange (I-CARE), U.S. Census Bureau 2020 Decennial Census

Age-standardised mortality rates for deaths involving coronavirus (COVID-19), non-COVID-19 deaths and all deaths by vaccination status, broken down by age group.

Flu vaccine uptake (percent) in at risk individuals aged 6 months to 65 years (excluding pregnant women), who received the flu vaccination between 1st September to the end of February as recorded in the GP record. The February collection has been adopted for our end of season figures from 2017 to 2018. All previous data is the same definitions but until the end of January rather than February to consider data returning from outside the practice and later in practice vaccinations.RationaleInfluenza (also known as Flu) is a highly infectious viral illness spread by droplet infection. The flu vaccination is offered to people who are at greater risk of developing serious complications if they catch the flu. The seasonal influenza programme for England is set out in the Annual Flu Letter. Both the flu letter and the flu plan have the support of the Chief Medical Officer (CMO), Chief Pharmaceutical Officer (CPhO), and Director of Nursing.Vaccination coverage is the best indicator of the level of protection a population will have against vaccine-preventable communicable diseases. Immunisation is one of the most effective healthcare interventions available, and flu vaccines can prevent illness and hospital admissions among these groups of people. Increasing the uptake of the flu vaccine among these high-risk groups should also contribute to easing winter pressure on primary care services and hospital admissions. Coverage is closely related to levels of disease. Monitoring coverage identifies possible drops in immunity before levels of disease rise.The UK Health Security Agency (UKHSA) will continue to provide expert advice and monitoring of public health, including immunisation. NHS England now has responsibility for commissioning the flu programme, and GPs continue to play a key role. NHS England teams will ensure that robust plans are in place locally and that high vaccination uptake levels are reached in the clinical risk groups. For more information, see the Green Book chapter 19 on Influenza.The Annual Flu Letter sets out the national vaccine uptake ambitions each year. In 2021 to 2022, the national ambition was to achieve at least 85 percent vaccine uptake in those aged 65 and over. Prior to this, the national vaccine uptake ambition was 75 percent, in line with WHO targets.Definition of numeratorNumerator is the number of vaccinations administered during the influenza season between 1st September and the end of February.Definition of denominatorDenominator is the GP registered population on the date of extraction including patients who have been offered the vaccine but refused it, as the uptake rate is measured against the overall eligible population. For more detailed information please see the user guide, available to view and download from https://www.gov.uk/government/collections/vaccine-uptake#seasonal-flu-vaccine-uptakeCaveatsRead codes are primarily used for data collection purposes to extract vaccine uptake data for patients who fall into one or more of the designated clinical risk groups. The codes identify individuals at risk, and therefore eligible for flu vaccination. However, it is important to note that there may be some individuals with conditions not specified in the recommended risk groups for vaccination, who may be offered influenza vaccine by their GP based on clinical judgement and according to advice contained in the flu letter and Green Book, and thus are likely to fall outside the listed Read codes. Therefore, this data should not be used for GP payment purposes.

NSSP Emergency Department (ED) Visit Trajectories by State and Sub-State Regions- COVID-19, Flu, RSV, Combined. This dataset provides the percentage of emergency department patient visits for the specified pathogen of all ED patient visits for the specified geographic part of the country that were observed for the given week from data submitted to the National Syndromic Surveillance Program (NSSP). In addition, the trend over time is characterized as increasing, decreasing or no change, with exceptions for when there are no data available, the data are too sparse, or there are not enough data to compute a trend. These data are to provide awareness of how the weekly trend is changing for the given geographic region.  Note that the reported sub-state trends are from Health Service Areas (HSA) and the data reported from the health care facilities located within the given HSA. Health Service Areas are regions of one or more counties that align to patterns of care seeking. The HSA level data are reported for each county in the HSA. More information on HSAs is available here. For the emergency department time series, trajectory classifications reported on for sub-state (HSA) emergency department time series, trajectory classifications are based on approximations of the first derivative (slope) of trends that are smoothed using generalized additive models (GAMs). To determine time intervals in which the slope is sufficiently changing (i.e., rate of change distinguishable from 0), 95% confidence intervals for the slope approximations are calculated and assessed. Weeks with a 95% confidence interval not containing 0 are classified as increasing if the slope estimate is positive and decreasing if the slope estimate is negative. Weeks with a 95% confidence interval containing 0 are classified as stable. In the scenario that an HSA's time series is determined to be too sparse (i.e., many weeks with percentages of 0%), a model is not fit, and the HSA is classified as “sparse”. For additional information, please see: Companion Guide: NSSP Emergency Department Data on Respiratory Illness Updated once per week on Fridays.

This dataset includes aggregated weekly influenza virus laboratory data that the Chicago Department of Public Health (CDPH) uses to monitor influenza activity and assess which influenza types and subtypes are circulating in Chicago. The data represent weekly positive influenza PCR tests voluntarily reported by network of several hospital laboratories in Chicago as well as two commercial laboratories serving Chicago facilities. The data includes positive test results by influenza type (influenza A and influenza B) as well as influenza A subtype (H3N2, H1N1pdm09) when available. These data do not include patient demographic or geographic information and represent both Chicago and non-Chicago residents tested by the reporting facility. Influenza laboratory data are available from the 2010-2011 season to present.

Two percentage fields are available in the dataset. Percentages are calculated for each characteristic group as follows:

The percentage of influenza types is calculated as the total number of positives tests for each influenza type divided by the total number of positive influenza tests reported (e.g., Influenza A/Influenza Positive). The percentage fields describe the percent of positive tests by influenza type each week (count_pct) and for the entire season to date (count_cum_pct).

The percentage of influenza A subtypes is calculated as the total number of positive tests for each influenza A subtype divided by the total number of positive influenza A tests reported (Influenza A Subtype/Influenza A). The percentage fields describe the percent of influenza A positive tests by subtype each week (count_pct) and for the entire season to date (count_cum_pct).

The percentage for characteristic group ‘Total Positive’ will always be 100% and does not represent influenza test positivity. For data on influenza test positivity see: https://data.cityofchicago.org/Health-Human-Services/Influenza-COVID-19-RSV-and-Other-Respiratory-Virus/qgdz-d5m4/about_data.

All data are provisional and subject to change. Information is updated as additional details are received. At any given time, this dataset reflects data currently known to CDPH. Numbers in this dataset may differ from other public sources.

Health and Safety Code section 1288.7(a) requires California acute care hospitals to offer influenza vaccine free of charge to all healthcare providers (HCP) or sign a declination form if a HCP chooses not to be vaccinated. Hospitals must report HCP influenza vaccination data to the California Department of Public Health (CDPH), including the percentage of HCP vaccinated. CDPH is required to make this information public on an annual basis [Health and Safety Code section 1288.8 (b)].

California acute care hospitals are required to offer free influenza vaccine to HCP. Hospital HCP must receive an annual vaccine or sign a declination form. Hospitals collect vaccination data for all HCP physically working in the hospital for at least one day during influenza season, regardless of clinical responsibility or patient contact. Hospitals report HCP vaccination rates to the California Department of Public Health (CDPH) and CDPH publishes the hospital results annually. CDPH reports data separately for hospital employees, licensed independent practitioners such as physicians, other contract staff, and trainees and volunteers (Health and Safety Code section 1288.7-1288.8).

Detailed information about the variables included in each dataset are described in the accompanying data dictionaries for the year of interest.

For general information about NHSN, surveillance definitions, and reporting requirements for HCP influenza vaccination, please visit: https://www.cdc.gov/nhsn/hps/vaccination/index.html

To link the CDPH facility IDs with those from other Departments, including OSHPD, please reference the "Licensed Facility Cross-Walk" Open Data table at: https://data.chhs.ca.gov/dataset/licensed-facility-crosswalk.

For information about healthcare personnel influenza vaccinations in California hospitals, please visit: https://www.cdph.ca.gov/Programs/CHCQ/HAI/Pages/HealthcarePersonnelInfluenzaVaccinationReportingInCA_Hospitals.aspx

Influenza B virus sequences from Australia and New Zealand, 2002–2013Tab delimited text file for 908 newly generated influenza B virus samples isolated from humans in Australia and New Zealand during 2002–2013. For each of these samples, virus sample name, collection data, country and GenBank accession numbers of each gene segment are provided.908_virus_accession.txtPrevalence percentageTab delimited text file providing percentages of viruses that were of type B in Australia (aus) and New Zealand (nz) and the three eastern states of Australia, New South Wales (nsw), Queensland (qld) and Victoria (vic). The percentage of viruses that were of Yamagata and Victoria lineages among all influenza B virus positive samples are provided for Australia (aus_yamagata and aus_victoria) and New Zealand (nz_yamagata and nz_victoria).Fig2_percentrage_prevalence.txtVirus accession numbersTab delimited text file for 908 newly generated influenza B virus samples isolated from humans in Australia and New Zealand during 2002–2013. For each of these samples, virus sample name, collection data, country and GenBank or GISAID accession numbers of each gene segment are provided.Virus_accession_numbers.txtBEAST xml file - B/VictoriaBeast input file (xml) with data and parameters used for Bayesian phylogenetic analysis of the HA dataset of B/Victoria viruses isolated in Australia and New Zealand.B_Victoria.xmlBEAST xml file - B/YamagataBeast input file (xml) with data and parameters used for Bayesian phylogenetic analysis of the HA dataset of B/Yamagata viruses isolated in Australia and New Zealand.B_Yamagata.xmlCases positive for influenza B virusesTab delimited text file providing patient age, country, date of sampling and lineage (Victoria or Yamagata) of 5260 influenza B viruses collected in Australia and New Zealand, 2002–2013cases.tsvHemagglutination inhibition titersExcel file with two sheets proving raw HI titer values for representative influenza B virus antigens of Victoria and Yamagata viruses isolated in Australia and New Zealand during 2002–2013 estimated against representative antisera. Strain names and passage history are provided for each antigen and antisera.HI_titers.xlsxPhylodynamic analysisBeast input file (xml) with data and parameters used to estimate epidemiological parameters (the effective reproductive number, Re) for each epidemic of virus lineages in Australia and New Zealand using the Birth-Death susceptible-infected-removed (BDSIR) model.BDSIR_analyses.zipPhylogeographic analysisBeast input file (xml) with data and parameters used to estimate counts of migration to and from Australia and New Zealand using the CTMC model.CTMC analyses.zip A complex interplay of viral, host and ecological factors shape the spatio-temporal incidence and evolution of human influenza viruses. Although considerable attention has been paid to influenza A viruses, a lack of equivalent data means that an integrated evolutionary and epidemiological framework has until now not been available for influenza B viruses, despite their significant disease burden. Through the analysis of over 900 full genomes from an epidemiological collection of more than 26,000 strains from Australia and New Zealand, we reveal fundamental differences in the phylodynamics of the two co-circulating lineages of influenza B virus (Victoria and Yamagata), showing that their individual dynamics are determined by a complex relationship between virus transmission, age of infection and receptor binding preference. In sum, this work identifies new factors that are important determinants of influenza B evolution and epidemiology.

This dataset has been archived and will no longer be updated as of 10/16/2024. For updated data, please refer to the ILINet State Activity Indicator Map.

Information on outpatient visits to health care providers for respiratory illness referred to as influenza-like illness (ILI) is collected through the U.S. Outpatient Influenza-like Illness Surveillance Network (ILINet). ILINet consists of outpatient healthcare providers in all 50 states, Puerto Rico, the District of Columbia, and the U.S. Virgin Islands. More than 100 million patient visits were reported during the 2022-23 season. Each week, more than 3,000 outpatient health care providers around the country report to CDC the number of patient visits for ILI by age group (0-4 years, 5-24 years, 25-49 years, 50-64 years, and ≥65 years) and the total number of visits for any reason. A subset of providers also reports total visits by age group. For this system, ILI is defined as fever (temperature of 100°F [37.8°C] or greater) and a cough and/or a sore throat. Activity levels are based on the percent of outpatient visits due to ILI in a jurisdiction compared to the average percent of ILI visits that occur during weeks with little or no influenza virus circulation (non-influenza weeks) in that jurisdiction. The number of sites reporting each week is variable; therefore, baselines are adjusted each week based on which sites within each jurisdiction provide data. To perform this adjustment, provider level baseline ILI ratios are calculated for those that have a sufficient reporting history. Providers that do not have the required reporting history to calculate a provider-specific baseline are assigned the baseline ratio for their practice type. The jurisdiction level baseline is then calculated using a weighted sum of the baseline ratios for each contributing provider.

The activity levels compare the mean reported percent of visits due to ILI during the current week to the mean reported percent of visits due to ILI during non-influenza weeks. The 13 activity levels correspond to the number of standard deviations below, at, or above the mean for the current week compared with the mean during non-influenza weeks. Activity levels are classified as minimal (levels 1-3), low (levels 4-5), moderate (levels 6-7), high (levels 8-10), and very high (levels 11-13). An activity level of 1 corresponds to an ILI percentage below the mean, level 2 corresponds to an ILI percentage less than 1 standard deviation above the mean, level 3 corresponds to an ILI percentage more than 1 but less than 2 standard deviations above the mean, and so on, with an activity level of 10 corresponding to an ILI percentage 8 to 11 standard deviations above the mean. The very high levels correspond to an ILI percentage 12 to 15 standard deviations above the mean for level 11, 16 to 19 standard deviations above the mean for level 12, and 20 or more standard deviations above the mean for level 13.

Disclaimers:

The ILI Activity Indicator map reflects the intensity of ILI activity, not the extent of geographic spread of ILI, within a jurisdiction. Therefore, outbreaks occurring in a single area could cause the entire jurisdiction to display high or very high activity levels. In addition, data collected in ILINet may disproportionally represent certain populations within a jurisdiction, and therefore, may not accurately depict the full picture of respiratory illness activity for the entire jurisdiction. Differences in the data presented here by CDC and independently by some health departments likely represent differing levels of data completeness with data presented by the health department likely being more complete.

More information is available on FluView Interactive.

Percent of tests positive for a pathogen is one of the surveillance metrics used to monitor respiratory pathogen transmission over time. The percent of tests positive is calculated by dividing the number of positive tests by the total number of tests administered, then multiplying by 100 [(# of positive tests/total tests) x 100]. These data include percent of tests positive values for the detection of severe acute respiratory virus coronavirus type 2 (SARS-CoV-2), the virus that causes COVID-19 and Respiratory syncytial virus (RSV) reported to the National Respiratory and Enteric Virus Surveillance System (NREVSS), a sentinel network of laboratories located through the US, includes clinical, public health and commercial laboratories; additional information available at: https://www.cdc.gov/surveillance/nrevss/index.html. Influenza results include clinical laboratory test results from NREVSS and U.S. World Health Organization collaborating laboratories; more details about influenza virologic surveillance are available here: https://www.cdc.gov/flu/weekly/overview.html. Data represent calculations based on laboratory tests performed, not individual people tested. RSV and COVID-19 are limited to nucleic acid amplification tests (NAATs), also listed as polymerase chain reaction tests (PCR). Participating laboratories report weekly to CDC the total number of RSV tests performed that week and the number of those tests that were positive. The RSV trend graphs display the national average of the weekly % test positivity for the current, previous, and following weeks in accordance with the recommendations for assessing RSV trends by percent (https://academic.oup.com/jid/article/216/3/345/3860464). All data are provisional and subject to change.

This dataset represents preliminary estimates of cumulative U.S. COVID-19 disease burden for the 2024-2025 period, including illnesses, outpatient visits, hospitalizations, and deaths. The weekly COVID-19-associated burden estimates are preliminary and based on continuously collected surveillance data from patients hospitalized with laboratory-confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections. The data come from the Coronavirus Disease 2019 (COVID-19)-Associated Hospitalization Surveillance Network (COVID-NET), a surveillance platform that captures data from hospitals that serve about 10% of the U.S. population. Each week CDC estimates a range (i.e., lower estimate and an upper estimate) of COVID-19 -associated burden that have occurred since October 1, 2024.

Note: Data are preliminary and subject to change as more data become available. Rates for recent COVID-19-associated hospital admissions are subject to reporting delays; as new data are received each week, previous rates are updated accordingly.

References

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2. Rolfes, MA, Foppa, IM, Garg, S, et al. Annual estimates of the burden of seasonal influenza in the United States: A tool for strengthening influenza surveillance and preparedness. Influenza Other Respi Viruses. 2018; 12: 132– 137. https://doi.org/10.1111/irv.12486
3. Tokars JI, Rolfes MA, Foppa IM, Reed C. An evaluation and update of methods for estimating the number of influenza cases averted by vaccination in the United States. Vaccine. 2018;36(48):7331-7337. doi:10.1016/j.vaccine.2018.10.026 
4. Collier SA, Deng L, Adam EA, Benedict KM, Beshearse EM, Blackstock AJ, Bruce BB, Derado G, Edens C, Fullerton KE, Gargano JW, Geissler AL, Hall AJ, Havelaar AH, Hill VR, Hoekstra RM, Reddy SC, Scallan E, Stokes EK, Yoder JS, Beach MJ. Estimate of Burden and Direct Healthcare Cost of Infectious Waterborne Disease in the United States. Emerg Infect Dis. 2021 Jan;27(1):140-149. doi: 10.3201/eid2701.190676. PMID: 33350905; PMCID: PMC7774540.
5. Reed C, Kim IK, Singleton JA,  et al. Estimated influenza illnesses and hospitalizations averted by vaccination–United States, 2013-14 influenza season. MMWR Morb Mortal Wkly Rep. 2014 Dec 12;63(49):1151-4. https://www.cdc.gov/mmwr/preview/mmwrhtml/mm6349a2.htm 
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*P-value < 0.05 from Chi-square test for independence of outcome across categories.aAt least one household index case with community-acquired influenza.bAt least one secondary case of influenza resulting from exposure to a household index case.cThe percent values presented are column percentages that add to 100 for each household characteristic.dThe percent values presented are row percentages with the corresponding cell in the All Households column as the denominator.eData missing for 24 households (3 with introduction of influenza, 1 of which resulted in secondary transmission).