BACKGROUND: Japanese encephalitis (JE) virus is the leading vaccine-preventable cause of encephalitis in Asia. For most travelers, JE risk is very low but varies based on several factors, including travel duration, location, and activities. To aid public health officials, health care providers, and travelers evaluate the worth of administering/ receiving pre-travel JE vaccinations, we estimated the numbers-needed-to-treat to prevent a case and the cost-effectiveness ratios of JE vaccination for U.S. travelers in different risk categories. METHODS: We used a decision tree model to estimate cost per case averted from a societal and traveler perspective for hypothetical cohorts of vaccinated and unvaccinated travelers. Risk Category I included travelers planning to spend >/=1 month in JE-endemic areas, Risk Category II were shorter-term (<1 month) travelers spending >/=20% of their time doing outdoor activities in rural areas, and Risk Category III were all remaining travelers. We performed sensitivity analyses including examining changes in cost-effectiveness with 10- and 100-fold increases in incidence and medical treatment costs. RESULTS: The numbers-needed-to-treat to prevent a case and cost per case averted were approximately 0.7 million and $0.6 billion for Risk Category I, 1.6 million and $1.2 billion for Risk Category II, and 9.8 million and $7.6 billion for Risk Category III. Increases of 10-fold and 100-fold in disease incidence proportionately decreased cost-effectiveness ratios. Similar levels of increases in medical treatment costs resulted in negligible changes in cost-effectiveness ratios. CONCLUSION: Numbers-needed-to-treat and cost-effectiveness ratios associated with preventing JE cases in U.S. travelers by vaccination varied greatly by risk category and disease incidence. While cost effectiveness ratios are not the sole rationale for decision-making regarding JE vaccination, the results presented here can aid in making such decisions under very different risk and cost scenarios.

In 2014/15 an Ebola outbreak of unprecedented dimensions afflicted the West African countries of Liberia, Guinea, and Sierra Leone. We performed a systematic review of manuscripts that forecasted the outbreak while it was occurring, and derive implications on the ways results could be interpreted by policy-makers. We reviewed 26 manuscripts, published between 2014 and April 2015, that presented forecasts of the West African Ebola outbreak. Forecasted case counts varied widely. An important determinant of forecast accuracy for case counts was how far into the future predictions were made. Generally, those that made forecasts less than 2 months into the future tended to be more accurate than those that made forecasts more than 10 weeks into the future. The exceptions were parsimonious statistical models in which the decay of the rate of spread of the pathogen among susceptible individuals was dealt with explicitly. Regarding future outbreaks, the most important lessons for policy makers when using similar modeling results are: i) uncertainty of forecasts will be higher in the beginning of the outbreak, ii) when data are limited, forecasts produced by models designed to inform specific decisions should be used in complimentary fashion for robust decision making - for this outbreak, two statistical models produced the most reliable case counts forecasts, but did not allow to understand the impact of interventions, while several compartmental models could estimate the impact of interventions but required data that was not available; iii) timely collection of essential data is necessary for optimal model use.

Objectives. To show how the Centers for Disease Control and Prevention's Pandemic Vaccine Campaign Planning Tool (PanVax Tool) can help state and local public health emergency planners demonstrate and quantify how partnerships with community vaccine providers can improve their overall pandemic vaccination program readiness.Methods. The PanVax Tool helps planners compare different strategies to vaccinate their jurisdiction's population in a severe pandemic by allowing users to customize the underlying model inputs in real time, including their jurisdiction's size, community vaccine provider types, and how they allocate vaccine to these providers. In this report, we used a case study with hypothetical data to illustrate how jurisdictions can utilize the PanVax Tool for preparedness planning.Results. By using the tool, planners are able to understand the impact of engaging with different vaccine providers in a vaccination campaign.Conclusions. The PanVax Tool is a useful tool to help demonstrate the impact of community vaccine provider partnerships on pandemic vaccination readiness and identify areas for improved partnerships for pandemic response.

BACKGROUND: In the event of a shigellosis outbreak in a childcare setting, exclusion policies are typically applied to afflicted children to limit shigellosis transmission. However, there is scarce evidence of their impact. METHODS: We evaluated five exclusion policies: Children return to childcare after: i) two consecutive laboratory tests (either PCR or culture) do not detect Shigella, ii) a single negative laboratory test (PCR or culture) does not detect Shigella, iii) seven days after beginning antimicrobial treatment, iv) after being symptom-free for 24 h, or v) 14 days after symptom onset. We also included four treatments to assess the policy options: i) immediate, effective treatment; ii) effective treatment after laboratory diagnosis; iii) no treatment; iv) ineffective treatment. Relying on published data, we calculated the likelihood that a child reentering childcare would be infectious, and the number of childcare-days lost per policy. RESULTS: Requiring two consecutive negative PCR tests yielded a probability of onward transmission of < 1%, with up to 17 childcare-days lost for children receiving effective treatment, and 53 days lost for those receiving ineffective treatment. CONCLUSIONS: Of the policies analyzed, requiring negative PCR testing before returning to childcare was the most effective to reduce the risk of shigellosis transmission, with one PCR test being the most effective for the least childcare-days lost.

BACKGROUND: West African countries Liberia, Sierra Leone, and Guinea experienced the largest and longest epidemic of Ebola virus disease from 2014 to 2016; after the epidemic was declared to be over, Liberia, Guinea, and Sierra Leone still experienced Ebola cases/clusters. The United States Centers for Disease Control and Prevention (US CDC) participated in the response efforts to the latter Ebola clusters, by assisting with case investigation, contact identification, and monitoring. This study aims to estimate the cost to the US CDC of responding to three different Ebola clusters after the end of the Ebola epidemic in 2015: i) Sierra Leone, Tonkolili (Jan 2016, 2 Ebola cases, 5 affected regions); ii) Guinea, Nzerekore (Mar-May 2016, 10 Ebola cases, 2 affected regions); iii) Liberia, Somali Drive (Mar 2016, 3 Ebola cases, 1 affected region). MAIN TEXT: After interviewing team members that had participated in the response, we estimated total costs (expressed in 2016 US Dollars [USD]), where total costs correspond to travel costs, deployed personnel costs, costs to prepare for deployment, procurement and interagency collaboration costs, among others. We also estimated cost per cluster case (corresponding to the total costs divided by the total number of cluster cases); and cost per case-affected-region (equal to the total costs divided by the product of the number of cases times the number of regions affected). We found that the response cost varied sixteenfold between USD 113 166 in Liberia and USD 1 764 271 in Guinea, where the main cost drivers were travel and personnel costs. The cost per cluster case varied tenfold between 37 722 in Liberia (three cases) and USD 347 226 in Sierra Leone, and the cost per case-affected-region varied threefold between USD 37 722 in Liberia and USD 88 214 in Guinea. CONCLUSIONS: Costs vary with the characteristics of each cluster, with those spanning more regions and cases requiring more resources for case investigation and contact identification and monitoring. These data will assist policy makers plan for similar post-epidemic responses.

Background: Many countries have acquired antiviral stockpiles for pandemic influenza mitigation and a significant part of the stockpile may be focussed towards community-based treatment. Methods: We developed a spreadsheet-based, decision tree model to assess outcomes averted and cost-effectiveness of antiviral treatment for outpatient use from the perspective of the healthcare payer in the UK. We defined five pandemic scenarios-one based on the 2009 A(H1N1) pandemic and four hypothetical scenarios varying in measures of transmissibility and severity. Results: Community-based antiviral treatment was estimated to avert 14-23% of hospitalizations in an overall population of 62.28 million. Higher proportions of averted outcomes were seen in patients with high-risk conditions, when compared to non-high-risk patients. We found that antiviral treatment was cost-saving across pandemic scenarios for high-risk population groups, and cost-saving for the overall population in higher severity influenza pandemics. Antiviral effectiveness had the greatest influence on both the number of hospitalizations averted and on cost-effectiveness. Conclusions: This analysis shows that across pandemic scenarios, antiviral treatment can be cost-saving for population groups at high risk of influenza-related complications.

Cost-effectiveness analysis (CEA), as noted by the Second Panel on Cost Effectiveness in Health and Medicine (herein, the Second Panel), “provides a framework for comparing the relative value of different interventions, along with information that can help decision makers sort through alternatives and decide which ones best serve their programmatic and financial needs.”1 The CEA, as well as other methods of economic evaluation, such as budgetary impact analysis and cost–benefit analysis, can inform health policy decisions. In 1996, the first Panel on Cost Effectiveness in Health and Medicine (herein, the First Panel) issued recommendations intended to improve the quality and comparability of CEA studies.2 The Second Panel has provided updated recommendations on the conduct, documentation, and reporting of CEAs with the same general intent.3

BACKGROUND: The 2014-2016 Ebola crisis in West Africa had approximately eight times as many reported deaths as the sum of all previous Ebola outbreaks. The outbreak magnitude and occurrence of multiple Ebola cases in at least seven countries beyond Liberia, Sierra Leone, and Guinea, hinted at the possibility of broad-scale transmission of Ebola. MAIN TEXT: Using a modeling tool developed by the US Centers for Disease Control and Prevention during the Ebola outbreak, we estimated the number of Ebola cases that might have occurred had the disease spread beyond the three countries in West Africa to cities in other countries at high risk for disease transmission (based on late 2014 air travel patterns). We estimated Ebola cases in three scenarios: a delayed response, a Liberia-like response, and a fast response scenario. Based on our estimates of the number of Ebola cases that could have occurred had Ebola spread to other countries beyond the West African foci, we emphasize the need for improved levels of preparedness and response to public health threats, which is the goal of the Global Health Security Agenda. Our estimates suggest that Ebola could have potentially spread widely beyond the West Africa foci, had local and international health workers and organizations not committed to a major response effort. Our results underscore the importance of rapid detection and initiation of an effective, organized response, and the challenges faced by countries with limited public health systems. Actionable lessons for strengthening local public health systems in countries at high risk of disease transmission include increasing health personnel, bolstering primary and critical healthcare facilities, developing public health infrastructure (e.g. laboratory capacity), and improving disease surveillance. With stronger local public health systems infectious disease outbreaks would still occur, but their rapid escalation would be considerably less likely, minimizing the impact of public health threats such as Ebola. CONCLUSIONS: The Ebola outbreak could have potentially spread to other countries, where limited public health surveillance and response capabilities may have resulted in additional foci. Health security requires robust local health systems that can rapidly detect and effectively respond to an infectious disease outbreak.

Using data from travelers to 4 countries in the Middle East, we estimated 3,250 (95% CI 1,300-6,600) severe cases of Middle East respiratory syndrome occurred in this region during September 2012-January 2016. This number is 2.3-fold higher than the number of laboratory-confirmed cases recorded in these countries.

Currently, there are mounting data suggesting that HIV-1 acquisition in women can be affected by the use of certain hormonal contraceptives. However, in non-human primate models, endogenous or exogenous progestin-dominant states are shown to increase acquisition. To gain mechanistic insights into this increased acquisition, we studied how mucosal barrier function and CD4+ T-cell and CD68+ macrophage density and localization changed in the presence of natural progestins or after injection with high-dose DMPA. The presence of natural or injected progestins increased virus penetration of the columnar epithelium and the infiltration of susceptible cells into a thinned squamous epithelium of the vaginal vault, increasing the likelihood of potential virus interactions with target cells. These data suggest that increasing either endogenous or exogenous progestin can alter female reproductive tract barrier properties and provide plausible mechanisms for increased HIV-1 acquisition risk in the presence of increased progestin levels.

To aid decision-making during CDC's response to the 2014-2016 Ebola virus disease (Ebola) epidemic in West Africa, CDC activated a Modeling Task Force to generate estimates on various topics related to the response in West Africa and the risk for importation of cases into the United States. Analysis of eight Ebola response modeling projects conducted during August 2014-July 2015 provided insight into the types of questions addressed by modeling, the impact of the estimates generated, and the difficulties encountered during the modeling. This time frame was selected to cover the three phases of the West African epidemic curve. Questions posed to the Modeling Task Force changed as the epidemic progressed. Initially, the task force was asked to estimate the number of cases that might occur if no interventions were implemented compared with cases that might occur if interventions were implemented; however, at the peak of the epidemic, the focus shifted to estimating resource needs for Ebola treatment units. Then, as the epidemic decelerated, requests for modeling changed to generating estimates of the potential number of sexually transmitted Ebola cases. Modeling to provide information for decision-making during the CDC Ebola response involved limited data, a short turnaround time, and difficulty communicating the modeling process, including assumptions and interpretation of results. Despite these challenges, modeling yielded estimates and projections that public health officials used to make key decisions regarding response strategy and resources required. The impact of modeling during the Ebola response demonstrates the usefulness of modeling in future responses, particularly in the early stages and when data are scarce. Future modeling can be enhanced by planning ahead for data needs and data sharing, and by open communication among modelers, scientists, and others to ensure that modeling and its limitations are more clearly understood. The activities summarized in this report would not have been possible without collaboration with many U.S. and international partners (http://www.cdc.gov/vhf/ebola/outbreaks/2014-west-africa/partners.html).

In 2012, an outbreak of infection with Middle East respiratory syndrome coronavirus (MERS-CoV), was detected in the Arabian Peninsula. Modeling can produce estimates of the expected annual number of symptomatic cases of MERS-CoV infection exported and the likelihood of exportation from source countries in the Middle East to countries outside the region.

BACKGROUND: After the detection of an Ebola virus disease outbreak in west Africa in 2014, one of the elements of the response was to contact trace and isolate patients in specialised Ebola treatment units (ETUs) at onset of fever. We aimed to assess the economic feasibility of administering preventive malaria treatment to all contacts of patients with Ebola virus disease, to prevent the onset of febrile malaria and subsequent admission to ETUs. METHODS: We used a decision tree model to analyse the costs of preventive malaria treatment (artemisinin-based combination treatment [ACT]) for all contacts of patients with Ebola virus disease (in terms of administration and averted ETU-stay costs) and benefits (in terms of averted ETU admissions) in west Africa, from a health-care provider perspective. The period of analyses was 1 year, which is roughly similar to the duration of the 2014-15 west Africa Ebola outbreak response. We calculated the intervention's cost per ETU admission averted (average cost-effectiveness ratio) by season (wet and dry), country (Liberia, Sierra Leone, and Guinea), and age of contact (<5 years, 5-14 years, and ≥15 years). We did sensitivity analyses to assess how results varied with malaria parasite prevalence (in children aged 2-10 years), daily cost of ETU stay (for Liberian malaria incidence levels), and compliance and effectiveness of preventive malaria treatment. FINDINGS: Administration of ACTs to contacts of patients with Ebola virus disease was cost saving for contacts of all ages in Liberia, Sierra Leone, and Guinea, in both seasons, from a health-care provider perspective. In the wet season, preventive malaria treatment was estimated to reduce the probability of a contact being admitted to an ETU by a maximum of 36% (in Guinea, for contacts aged <5 years), and a minimum of 10% (in Guinea and Sierra Leone, for those aged ≥15 years). Assuming 85% compliance and taking into account the African population pyramid, the intervention is expected to be cost saving in contacts of all age groups in areas with malaria parasite prevalence in children aged 2-10 years as low as 10%. In Liberia during the wet season, malaria preventive treatment was cost saving even when average daily bed-stay costs were as low as US$5 for children younger than 5 years, $9 for those aged 5-14 years, and $22 for those aged 15 years or older. INTERPRETATION: Administration of preventive malaria treatment to contacts of patients with Ebola virus disease should be considered by public health officials when addressing Ebola virus disease outbreaks in countries and seasons where malaria reaches high levels of transmission. FUNDING: Centers for Disease Control and Prevention.

BACKGROUND: Seasonal influenza causes considerable morbidity and mortality across all age groups, and influenza vaccination was recommended in 2010 for all persons aged 6 months and above. We estimated the averted costs due to influenza vaccination, taking into account the seasonal economic burden of the disease. METHODS: We used recently published values for averted outcomes due to influenza vaccination for influenza seasons 2005-06, 2006-07, 2007-08, and 2008-09, and age cohorts 6 months-4 years, 5-19 years, 20-64 years, and 65 years and above. Costs were calculated according to a payer and societal perspective (in 2009 US$), and took into account medical costs and productivity losses. RESULTS: When taking into account direct medical costs (payer perspective), influenza vaccination was cost saving only for the older age group (65≥) in seasons 2005-06 and 2007-08. Using the same perspective, influenza vaccination resulted in total costs of $US 1.7 billion (95%CI: $US 0.3-4.0 billion) in 2006-07 and $US 1.8 billion (95%CI: $US 0.1-4.1 billion) in 2008-09. When taking into account a societal perspective (and including the averted lost earnings due to premature death) averted deaths in the older age group influenced the results, resulting in cost savings for all ages combined in season 07-08. DISCUSSION: Influenza vaccination was cost saving in the older age group (65≥) when taking into account productivity losses and, in some seasons, when taking into account medical costs only. Averted costs vary significantly per season; however, in seasons where the averted burden of deaths is high in the older age group, averted productivity losses due to premature death tilt overall seasonal results towards savings. Indirect vaccination effects and the possibility of diminished case severity due to influenza vaccination were not considered, thus the averted burden due to influenza vaccine may be even greater than reported.

BACKGROUND: To inform planning for an influenza pandemic, we estimated US demand for N95 filtering facepiece respirators (respirators) by healthcare and emergency services personnel and need for surgical masks by pandemic patients seeking care. METHODS: We used a spreadsheet-based model to estimate demand for 3 scenarios of respirator use: base case (usage approximately follows epidemic curve), intermediate demand (usage rises to epidemic peak and then remains constant), and maximum demand (all healthcare workers use respirators from pandemic onset). We assumed that in the base case scenario, up to 16 respirators would be required per day per intensive care unit patient and 8 per day per general ward patient. Outpatient healthcare workers and emergency services personnel would require 4 respirators per day. Patients would require 1.2 surgical masks per day. RESULTS AND CONCLUSIONS: Assuming that 20% to 30% of the population would become ill, 1.7 to 3.5 billion respirators would be needed in the base case scenario, 2.6 to 4.3 billion in the intermediate demand scenario, and up to 7.3 billion in the maximum demand scenario (for all scenarios, between 0.1 and 0.4 billion surgical masks would be required for patients). For pandemics with a lower attack rate and fewer cases (eg, 2009-like pandemic), the number of respirators needed would be higher because the pandemic would have longer duration. Providing these numbers of respirators and surgical masks represents a logistic challenge for US public health agencies. Public health officials must urgently consider alternative use strategies for respirators and surgical masks during a pandemic that may vary from current practices.

BACKGROUND: Excess mortality due to seasonal influenza is substantial, yet quantitative estimates of the benefit of annual vaccination programs on influenza-associated mortality are lacking. METHODS: We estimated the numbers of deaths averted by vaccination in four age groups (0.5 to 4, 5 to 19, 20 to 64 and ≥65 yrs.) for the nine influenza seasons from 2005/6 through 2013/14. These estimates were obtained using a Monte Carlo approach applied to weekly U.S. age group-specific estimates of influenza-associated excess mortality, monthly vaccination coverage estimates and summary seasonal influenza vaccine effectiveness estimates to obtain estimates of the number of deaths averted by vaccination. The estimates are conservative as they do not include indirect vaccination effects. RESULTS: From August, 2005 through June, 2014, we estimated that 40,127 (95% confidence interval [CI] 25,694 to 59,210) deaths were averted by influenza vaccination. We found that of all studied seasons the most deaths were averted by influenza vaccination during the 2012/13 season (9398; 95% CI 2,386 to 19,897) and the fewest during the 2009/10 pandemic (222; 95% CI 79 to 347). Of all influenza-associated deaths averted, 88.9% (95% CI 83 to 92.5%) were in people ≥65 yrs. old. CONCLUSIONS: The estimated number of deaths averted by the US annual influenza vaccination program is considerable, especially among elderly adults and even when vaccine effectiveness is modest, such as in the 2012/13 season. As indirect effects ("herd immunity") of vaccination are ignored, these estimates represent lower bound estimates and are thus conservative given valid excess mortality estimates.

BACKGROUND: Vaccination has been increasingly promoted to help control epidemic and endemic typhoid fever in high-incidence areas. Despite growing recognition that typhoid incidence in some areas of sub-Saharan Africa is similar to high-incidence areas of Asia, no large-scale typhoid vaccination campaigns have been conducted there. We performed an economic evaluation of a hypothetical one-time, fixed-post typhoid vaccination campaign in Kasese, a rural district in Uganda where a large, multi-year outbreak of typhoid fever has been reported. METHODS: We used medical cost and epidemiological data retrieved on-site and campaign costs from previous fixed-post vaccination campaigns in Kasese to account for costs from a public sector health care delivery perspective. We calculated program costs and averted disability-adjusted life years (DALYs) and medical costs as a result of vaccination, to calculate the cost of intervention per DALY and case averted. RESULTS: Over the 3 years of projected vaccine efficacy, a one-time vaccination campaign was estimated to avert 1768 (684-4431) typhoid fever cases per year and a total of 3868 (1353-9807) DALYs over the duration of the immunity conferred by the vaccine. The cost of the intervention per DALY averted was US$ 484 (18-1292) and per case averted US$ 340 (13-881). CONCLUSION: We estimated the vaccination campaign in this setting to be highly cost-effective, according to WHO's cost-effective guidelines. Results may be applicable to other African settings with similar high disease incidence estimates.