Charisma Y. Atkins

Estimating the Burden of 2009 Pandemic Influenza A (H1N1) in the United States (April 2009–April 2010)

To calculate the burden of 2009 pandemic influenza A (pH1N1) in the United States, we extrapolated from the Centers for Disease Control and Preventions Emerging Infections Program laboratory-confirmed hospitalizations across the entire United States, and then corrected for underreporting. From 12 April 2009 to 10 April 2010, we estimate that approximately 60.8 million cases (range: 43.3-89.3 million), 274,304 hospitalizations (195,086-402,719), and 12,469 deaths (8868-18,306) occurred in the United States due to pH1N1. Eighty-seven percent of deaths occurred in those under 65 years of age with children and working adults having risks of hospitalization and death 4 to 7 times and 8 to 12 times greater, respectively, than estimates of impact due to seasonal influenza covering the years 1976-2001. In our study, adults 65 years of age or older were found to have rates of hospitalization and death that were up to 75% and 81%, respectively, lower than seasonal influenza. These results confirm the necessity of a concerted public health response to pH1N1.

Effects of Vaccine Program against Pandemic Influenza A(H1N1) Virus, United States, 2009–2010

Vaccination likely prevented 700,000–1,500,000 clinical cases, 4,000–10,000 hospitalizations, and 200–500 deaths.

Estimating Effect of Antiviral Drug Use during Pandemic (H1N1) 2009 Outbreak, United States

From April 2009 through March 2010, during the pandemic (H1N1) 2009 outbreak, ≈8.2 million prescriptions for influenza neuraminidase-inhibiting antiviral drugs were filled in the United States. We estimated the number of hospitalizations likely averted due to use of these antiviral medications. After adjusting for prescriptions that were used for prophylaxis and personal stockpiles, as well as for patients who did not complete their drug regimen, we estimated the filled prescriptions prevented ≈8,400–12,600 hospitalizations (on the basis of median values). Approximately 60% of these prevented hospitalizations were among adults 18–64 years of age, with the remainder almost equally divided between children 0–17 years of age and adults >65 years of age. Public health officials should consider these estimates an indication of success of treating patients during the 2009 pandemic and a warning of the need for renewed planning to cope with the next pandemic.

Standardizing Scenarios to Assess the Need to Respond to an Influenza Pandemic

An outbreak of human infections with an avian influenza A(H7N9) virus was first reported in eastern China by the World Health Organization on 1 April 2013 [1]. This novel influenza virus was fatal in approximately one-third of the 135 confirmed cases detected in the 4 months following its initial identification [2], and limited human-to-human H7N9 virus transmission could not be excluded in some Chinese clusters of cases [3, 4]. There was, and still is, the possibility that the virus would mutate to the point where there would be sustained human-to-human transmission. Given that most of the human population has no prior immunity (either due to natural challenge or vaccine induced), such a strain presents the danger of starting an influenza pandemic. In response to such a threat, the Joint Modeling Unit at the Centers for Disease Control and Prevention (CDC) was asked to conduct a rapid assessment of both the potential burden of unmitigated disease and the possible impacts of different mitigation measures. We were tasked to evaluate the 6 following interventions: invasive mechanical ventilators, influenza antiviral drugs for treatment (but not large-scale prophylaxis), influenza vaccines, respiratory protective devices for healthcare workers and surgical face masks for patients, school closings to reduce transmission, and airport-based screening to identify those ill with novel influenza virus entering the United States. This supplement presents reports on the methods and estimates for the first 5 listed interventions, and in this introduction we outline the general approach and standardized epidemiological assumptions used in all the articles.

Estimating Ebola Treatment Needs, United States.

To the Editor: By December 31, 2014, the Ebola epidemic in West Africa had resulted in treatment of 10 Ebola case-patients in the United States; a maximum of 4 patients received treatment at any one time (1). Four of these 10 persons became clinically ill in the United States (2 infected outside the United States and 2 infected in the United States), and 6 were clinically ill persons medically evacuated from West Africa (Technical Appendix 1 Table 6). To plan for possible future cases in the United States, policy makers requested we produce a tool to estimate future numbers of Ebola case-patients needing treatment at any one time in the United States. Gomes et al. previously estimated the potential size of outbreaks in the United States and other countries for 2 different dates in September 2014 (2). Another study considered the overall risk for exportation of Ebola from West Africa but did not estimate the number of potential cases in the United States at any one time (3). We provide for practicing public health officials a spreadsheet-based tool, Beds for Ebola Disease (BED) (Technical Appendix 2) that can be used to estimate the number of Ebola patients expected to be treated simultaneously in the United States at any point in time. Users of BED can update estimates for changing conditions and improved quality of input data, such as incidence of disease. The BED tool extends the work of prior studies by dividing persons arriving from Liberia, Sierra Leone, and Guinea into the following 3 categories: 1) travelers who are not health care workers (HCWs), 2) HCWs, and 3) medical evacuees. This categorization helps public health officials assess the potential risk for Ebola virus infection in individual travelers and the subsequent need for post-arrival monitoring (4). We used the BED tool to calculate the estimated number of Ebola cases at any one time in the United States by multiplying the rate of new infections in the United States by length of stay (LOS) in hospital (Table). The rate of new infections is the sum of the rate of infected persons in the 3 listed categories who enter the United States from Liberia, Sierra Leone, or Guinea. For the first 2 categories of travelers, low and high estimates of Ebola-infected persons arriving in the United States are calculated by using low and high estimates of both the incidence of disease in the 3 countries and the number of arrivals per month (Table). Calculating the incidence among arriving HCWs required estimating the number of HCWs treating Ebola patients in West Africa (Technical Appendix 1, Tables 2–4). For medical evacuations of persons already ill from Ebola, we calculated low and high estimates using unpublished data of such evacuations through the end of December 2014. Table Calculated monthly rates of Ebola disease among persons arriving in the United States and additional secondary cases, 2014 Although only 1 Ebola case has caused additional cases in the United States (7), we included the possibility that each Ebola case-patient who traveled into the United States would cause either 0 secondary cases (low estimate) or 2 secondary cases (high estimate) (Table). Such transmission might occur before a clinically ill traveler is hospitalized or between a patient and HCWs treating the patient (7). To account for the possibility that infected travelers may arrive in clusters, we assumed that persons requiring treatment would be distributed according to a Poisson probability distribution. Using this distribution enables us to calculate, using the BED tool, 95% CIs around the average estimate of arriving case-patients. The treatment length used in both the low and high estimate calculations was 14.8 days, calculated as a weighted average of the LOS of hospitalized case-patients treated in West Africa through September 2014 (Technical Appendix 1 Table 5) (8). We conducted a sensitivity analysis using LOS and reduced case-fatality rate of patients treated in the United States (Technical Appendix 1 Table 6). For late 2014, the low estimate of the average number of beds needed to treat patients with Ebola at any point in time was 1 (95% CI 0–3). The high estimate was 7 (95% CI 2–13). In late 2014, the United States had to plan and prepare to treat additional Ebola case-patients. By mid-January 2015, the capacity of Ebola treatment centers in the United States (49 hospitals with 71 total beds [9]) was sufficient to care for our highest estimated number of Ebola patients. Policymakers already have used the BED model to evaluate responses to the risk for arrival of Ebola virus–infected travelers, and it can be used in future infectious disease outbreaks of international origin to plan for persons requiring treatment within the United States. Technical Appendix 1: Data inputs and assumptions; sensitivity analysis (length of stay and case-fatality rate); comparison with other published estimates; and limitations. Click here to view.(228K, pdf) Technical Appendix 2: Beds for Ebola Disease (BED) model. Click here to view.(161K, xlsx)

Cost-Effectiveness Evaluation of a Novel Integrated Bite Case Management Program for the Control of Human Rabies, Haiti 2014–2015

Haiti has the highest burden of rabies in the Western hemisphere, with 130 estimated annual deaths. We present the cost-effectiveness evaluation of an integrated bite case management program combining community bite investigations and passive animal rabies surveillance, using a governmental perspective. The Haiti Animal Rabies Surveillance Program (HARSP) was first implemented in three communes of the West Department, Haiti. Our evaluation encompassed all individuals exposed to rabies in the study area (N = 2,289) in 2014–2015. Costs (2014 U.S. dollars) included diagnostic laboratory development, training of surveillance officers, operational costs, and postexposure prophylaxis (PEP). We used estimated deaths averted and years of life gained (YLG) from prevented rabies as health outcomes. HARSP had higher overall costs (range:

Cost-effectiveness of alternative strategies for annual influenza vaccination among children aged 6 months to 14 years in four provinces in China.

39,568–

Modeling in Real Time During the Ebola Response

80,290) than the no-bite-case-management (NBCM) scenario (

Cost-effectiveness of preventing dental caries and full mouth dental reconstructions among Alaska Native children in the Yukon–Kuskokwim delta region of Alaska

15,988–

Cost-effectiveness of dog rabies vaccination programs in East Africa

26,976), partly from an increased number of bite victims receiving PEP. But HARSP had better health outcomes than NBCM, with estimated 11 additional annual averted deaths in 2014 and nine in 2015, and 654 additional YLG in 2014 and 535 in 2015. Overall, HARSP was more cost-effective (US