Global measles vaccine coverage has stagnated at approximately 85% for over a decade. By simplifying vaccine logistics and administration, the measles and rubella microarray patch (MR-MAP) may improve coverage. Clinical trials have demonstrated similar safety and immunogenicity in 9-month-old infants for MR-MAPs compared with syringe-and-needle vaccination. To aid commercialization, we present estimates of MR-MAP demand. We created a spreadsheet-based tool to estimate demand for MR-MAPs using data from 180 WHO countries during 2000-2016. Five immunization scenarios were analyzed: (1a) Supplementary Immunization Activities (SIAs) in Gavi, the Vaccine Alliance (Gavi)-eligible countries and (1b) WHO countries where preventive SIAs are routinely conducted; (2) SIAs and outbreak response immunization in all WHO countries; (3) routine immunization (RI) and SIAs in six high-burden measles countries (the Democratic Republic of the Congo, Ethiopia, India, Indonesia, Nigeria, and Pakistan); (4) RI and SIAs in six high-burden countries and Gavi-eligible countries; and (5) hard-to-reach populations. MR-MAP demand varied greatly across scenarios. Forecasts for 2025-2034 estimate from 137 million doses in hard-to-reach populations (scenario 5) to 2.587 billion doses for RI and SIAs in six high-burden countries and Gavi-eligible countries (scenario 4). When policymakers and manufacturers assess MR-MAP demand, they may consider multiple scenarios to allow for a complete consideration of potential markets and public health needs.

Case investigation and contact tracing (CICT) are public health measures that aim to break the chain of pathogen transmission. Changes in viral characteristics of COVID-19 variants have likely affected the effectiveness of CICT programs. We estimated and compared the cases averted in Vermont when the original COVID-19 strain circulated (Nov. 25, 2020-Jan. 19, 2021) with two periods when the Delta strain dominated (Aug. 1-Sept. 25, 2021, and Sept. 26-Nov. 20, 2021). When the original strain circulated, we estimated that CICT prevented 7180 cases (55% reduction in disease burden), compared to 1437 (15% reduction) and 9970 cases (40% reduction) when the Delta strain circulated. Despite the Delta variant being more infectious and having a shorter latency period, CICT remained an effective tool to slow spread of COVID-19; while these viral characteristics did diminish CICT effectiveness, non-viral characteristics had a much greater impact on CICT effectiveness.

BACKGROUND: Facing a surge of COVID-19 cases in late August 2021, the U.S. state of Illinois re-enacted its COVID-19 mask mandate for the general public and issued a requirement for workers in certain professions to be vaccinated against COVID-19 or undergo weekly testing. The mask mandate required any individual, regardless of their vaccination status, to wear a well-fitting mask in an indoor setting. METHODS: We used Illinois Department of Public Health's COVID-19 confirmed case and vaccination data and investigated scenarios where masking and vaccination would have been reduced to mimic what would have happened had the mask mandate or vaccine requirement not been put in place. The study examined a range of potential reductions in masking and vaccination mimicking potential scenarios had the mask mandate or vaccine requirement not been enacted. We estimated COVID-19 cases and hospitalizations averted by changes in masking and vaccination during the period covering October 20 to December 20, 2021. RESULTS: We find that the announcement and implementation of a mask mandate are likely to correlate with a strong protective effect at reducing COVID-19 burden and the announcement of a vaccinate-or-test requirement among frontline professionals is likely to correlate with a more modest protective effect at reducing COVID-19 burden. In our most conservative scenario, we estimated that from the period of October 20 to December 20, 2021, the mask mandate likely prevented approximately 58,000 cases and 1,175 hospitalizations, while the vaccinate-or-test requirement may have prevented at most approximately 24,000 cases and 475 hospitalizations. CONCLUSION: Our results indicate that mask mandates and vaccine-or-test requirements are vital in mitigating the burden of COVID-19 during surges of the virus.

INTRODUCTION: During the COVID-19 pandemic, the U.S. Centers for Disease Control and Prevention developed a simple spreadsheet-based tool to help state and local public health officials assess the performance and impact of COVID-19 case investigation and contact tracing in their jurisdiction. The applicability and feasibility of building such a tool for sexually transmitted diseases were assessed. METHODS: The key epidemiologic differences between sexually transmitted diseases and respiratory diseases (e.g., mixing patterns, incubation period, duration of infection, and the availability of treatment) were identified, and their implications for modeling case investigation and contact tracing impact with a simple spreadsheet tool were remarked on. Existing features of the COVID-19 tool that are applicable for evaluating the impact of case investigation and contact tracing for sexually transmitted diseases were also identified. RESULTS: Our findings offer recommendations for the future development of a spreadsheet-based modeling tool for evaluating the impact of sexually transmitted disease case investigation and contact tracing efforts. Generally, we advocate for simplifying sexually transmitted disease-specific complexities and performing sensitivity analyses to assess uncertainty. The authors also acknowledge that more complex modeling approaches might be required but note that it is possible that a sexually transmitted disease case investigation and contact tracing tool could incorporate features from more complex models while maintaining a user-friendly interface. CONCLUSIONS: A sexually transmitted disease case investigation and contact tracing tool could benefit from the incorporation of key features of the COVID-19 model, namely its user-friendly interface. The inherent differences between sexually transmitted diseases and respiratory viruses should not be seen as a limitation to the development of such tool.

Context The implementation of case investigation and contact tracing (CICT) for controlling COVID-19 (caused by SARS-Cov-2 virus) has proven challenging due to varying levels of public acceptance and initially constrained resources, especially enough trained staff. Evaluating the impacts of CICT will aid efforts to improve such programs.Objectives Estimate the number of COVID-19 cases and hospitalizations averted by CICT and identify CICT processes that could improve overall effectiveness.Design We used data on proportion of cases interviewed, contacts notified or monitored, and days from testing to contact notification from 14 jurisdictions to model the impact of CICT on cumulative cases counts and hospitalizations over a 60-day period. Using the Centers for Disease Control and Prevention (CDC)’s COVIDTracer tool, we estimated a range of impacts by assuming either contacts would quarantine only if monitored or would do so upon notification of potential exposure. We also varied the observed program metrics to assess their relative influence.Results Performance by jurisdictions varied widely. Jurisdictions isolated between 12 and 86% of cases (including contacts which became cases) within 6 to 10 days after exposure-and-infection. We estimated that CICT-related reductions in transmission ranged from 0.4% to 32%. For every 100 cases prevented by nonpharmaceutical interventions, CICT averted between 4 and 97 additional cases. Reducing time to case isolation by one day increased averted case estimates by up to 15 percentage points. Increasing the proportion of cases interviewed or contacts notified by 20 percentage points each resulted in at most 3 or 6 percentage point improvements in averted cases.Conclusions We estimated that case investigation and contact tracing reduced the number of COVID-19 cases and hospitalizations among all jurisdictions studied. Reducing time to isolation produced the greatest improvements in impact of CICT.Competing Interest StatementThe authors have declared no competing interest.Funding StatementThis work was performed as part of the official duties of all participants in support of the US CDC's COVID-19 Response.Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesThe details of the IRB/oversight body that provided approval or exemption for the research described are given below:This activity was reviewed by CDC and was conducted consistent with applicable federal law and CDC policy.All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesData is available upon request

Emerging epidemics are challenging to track. Only a subset of cases is recognized and reported, as seen with the Zika virus (ZIKV) epidemic where large proportions of infection were asymptomatic. However, multiple imperfect indicators of infection provide an opportunity to estimate the underlying incidence of infection. We developed a modeling approach that integrates a generic Time-series Susceptible-Infected-Recovered epidemic model with assumptions about reporting biases in a Bayesian framework and applied it to the 2016 Zika epidemic in Puerto Rico using three indicators: suspected arboviral cases, suspected Zika-associated Guillain-Barré Syndrome cases, and blood bank data. Using this combination of surveillance data, we estimated the peak of the epidemic occurred during the week of August 15, 2016 (the 33rd week of year), and 120 to 140 (50% credible interval [CrI], 95% CrI: 97 to 170) weekly infections per 10,000 population occurred at the peak. By the end of 2016, we estimated that approximately 890,000 (95% CrI: 660,000 to 1,100,000) individuals were infected in 2016 (26%, 95% CrI: 19% to 33%, of the population infected). Utilizing multiple indicators offers the opportunity for real-time and retrospective situational awareness to support epidemic preparedness and response.Competing Interest StatementThe authors have declared no competing interest.Funding StatementThe author(s) received no specific funding for this work.Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesThe details of the IRB/oversight body that provided approval or exemption for the research described are given below:Exemption was obtained from the CDC Human Subjects Research Office as the data were collected as part of regular surveillance activities.All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesAll relevant data are within the manuscript and its Supporting Information files.

Importance: Evidence of the impact of COVID-19 Case Investigation and Contact Tracing (CICT) programs is lacking. Policymakers need this evidence to assess its value. Objective(s): Estimate COVID-19 cases and hospitalizations averted nationwide by US states' CICT programs. Design(s): We combined data from US CICT programs (e.g., proportion of cases interviewed, contacts notified or monitored, and days to case and contact notification) with incidence data to model CICT impacts over 60 days period (November 25, 2020 to January 23, 2021) during the height of the pandemic. We estimated a range of impacts by varying assumed compliance with isolation and quarantine recommendations. Setting(s): US States and Territories Participants: Fifty-nine state and territorial health departments that received federal funding supporting COVID-19 pandemic response activities were eligible for inclusion. Of these, 22 states and 1 territory reported all measures necessary for the analysis. These 23 jurisdictions covered 42.5% of the US population (140 million persons), spanned all 4 census regions, and reported data that reflected all 59 federally funded CICT programs. Intervention(s): Public health case investigation and contact tracing Main Outcomes and Measures: Cases and hospitalizations averted; percent of cases averted among cases not prevented by vaccination and other non-pharmaceutical interventions (other NPIs). Result(s): We estimated 1.11 million cases and 27,231 hospitalizations were averted by CICT programs under a scenario where 80% of interviewed cases and monitored contacts, and 30% of notified contacts fully complied with isolation and quarantine guidance, eliminating their contributions to future transmission. As many as 1.36 million cases and 33,527 hospitalizations could have been prevented if all interviewed cases and monitored contacts had entered into and fully complied with isolation and quarantine guidelines upon being interviewed or notified. Across all scenarios and jurisdictions, CICT averted a median of 21.2% (range: 1.3% - 65.8%) of the cases not prevented by vaccination and other NPIs. Conclusions and Relevance: CICT programs likely had a substantial role in curtailing the pandemic in most jurisdictions during the winter 2020-2021 peak. Differences in impact across jurisdictions indicate an opportunity to further improve CICT effectiveness. These estimates demonstrate the potential benefits from sustaining and improving these programs. Copyright The copyright holder for this preprint is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-ND 4.0 International license.

Researchers have documented that vacant lot greening can reduce community-level crime and violence. Busy Streets Theory (BST) suggests that residents who are involved in the greening process can help to improve physical environments and build social connections that deter crime and violence. Yet few researchers have explored how community engagement in the greening process may affect crime and violence outcomes. We applied BST to test the effects of community-engaged vacant lot greening compared to vacant lots that received either professional mowing or no treatment, on the density of violent crime around study lots. Using mixed effects regression models, we analyzed trends in violent crime density over the summer months from 2016 to 2018 at 2102 street segments in Youngstown, OH. These street segments fell within 150meters of an intervention parcel that was classified as one of three conditions: community-engaged maintenance, professional mowing, or no treatment (control). We found that street segments in areas receiving community-engaged maintenance or professional mowing experienced greater declines in violent crime density than street segments in areas receiving no treatment, and more decline occurred in the community-engaged condition compared to the professional mow condition. Our findings support BST and suggest that community-engaged greening of vacant lots in postindustrial cities with a concentrated vacancy can reduce crime and violence.

Quantifying the effect of public health actions on population health is essential when justifying sustained public health investment. Using modeling, we conservatively estimated that rapid response to a multistate foodborne outbreak of Salmonella Typhimurium in the United States in 2018 potentially averted 94 reported cases and $633,181 in medical costs and productivity losses.

IMPORTANCE: Evidence of the impact of COVID-19 case investigation and contact tracing (CICT) programs is lacking, but policy makers need this evidence to assess the value of such programs. OBJECTIVE: To estimate COVID-19 cases and hospitalizations averted nationwide by US states' CICT programs. DESIGN, SETTING, AND PARTICIPANTS: This decision analytical model study used combined data from US CICT programs (eg, proportion of cases interviewed, contacts notified or monitored, and days to case and contact notification) with incidence data to model outcomes of CICT over a 60-day period (November 25, 2020, to January 23, 2021). The study estimated a range of outcomes by varying assumed compliance with isolation and quarantine recommendations. Fifty-nine state and territorial health departments that received federal funding supporting COVID-19 pandemic response activities were eligible for inclusion. Data analysis was performed from July to September 2021. EXPOSURE: Public health case investigation and contact tracing. MAIN OUTCOMES AND MEASURES: The primary outcomes were numbers of cases and hospitalizations averted and the percentage of cases averted among cases not prevented by vaccination and other nonpharmaceutical interventions. RESULTS: In total, 22 states and 1 territory reported all measures necessary for the analysis. These 23 jurisdictions covered 42.5% of the US population (approximately 140 million persons), spanned all 4 US Census regions, and reported data that reflected all 59 federally funded CICT programs. This study estimated that 1.11 million cases and 27 231 hospitalizations were averted by CICT programs under a scenario where 80% of interviewed cases and monitored contacts and 30% of notified contacts fully complied with isolation and quarantine guidance, eliminating their contributions to future transmission. As many as 1.36 million cases and 33 527 hospitalizations could have been prevented if all interviewed cases and monitored contacts had entered into and fully complied with isolation and quarantine guidelines upon being interviewed or notified. Across both scenarios and all jurisdictions, CICT averted an estimated median of 21.2% (range, 1.3%-65.8%) of the cases not prevented by vaccination and other nonpharmaceutical interventions. CONCLUSIONS AND RELEVANCE: These findings suggest that CICT programs likely had a substantial role in curtailing the pandemic in most jurisdictions during the 2020 to 2021 winter peak. Differences in outcomes across jurisdictions indicate an opportunity to further improve CICT effectiveness. These estimates demonstrate the potential benefits from sustaining and improving these programs.

CONTEXT: The implementation of case investigation and contact tracing (CICT) for controlling COVID-19 (caused by SARS-CoV-2 virus) has proven challenging due to varying levels of public acceptance and initially constrained resources, especially enough trained staff. Evaluating the impacts of CICT will aid efforts to improve such programs. OBJECTIVES: Estimate the number of COVID-19 cases and hospitalizations averted by CICT and identify CICT processes that could improve overall effectiveness. DESIGN: We used data on the proportion of cases interviewed, contacts notified or monitored, and days from testing to case and contact notification from 14 jurisdictions to model the impact of CICT on cumulative case counts and hospitalizations over a 60-day period. Using the Centers for Disease Control and Prevention's COVIDTracer Advanced tool, we estimated a range of impacts by assuming either contacts would quarantine only if monitored or would do so upon notification of potential exposure. We also varied the observed program metrics to assess their relative influence. RESULTS: Performance by jurisdictions varied widely. Jurisdictions isolated between 12% and 86% of cases (including contacts that became cases) within 6 to 10 days after infection. We estimated that CICT-related reductions in transmission ranged from 0.4% to 32%. For every 100 remaining cases after other nonpharmaceutical interventions were implemented, CICT averted between 4 and 97 additional cases. Reducing time to case isolation by 1 day increased averted case estimates by up to 15 percentage points. Increasing the proportion of cases interviewed or contacts notified by 20 percentage points each resulted in at most 3 or 6 percentage point improvements in averted cases. CONCLUSIONS: We estimated that CICT reduced the number of COVID-19 cases and hospitalizations among all jurisdictions studied. Reducing time to isolation produced the greatest improvements in impact of CICT.

BACKGROUND: Schools are an integral part of the community; however, congregate settings facilitate transmission of SARS-CoV-2, presenting a challenge to school administrators to provide a safe, in-school environment for students and staff. METHODS: We adapted the Centers for Disease Control and Prevention's COVIDTracer Advanced tool to model the transmission of SARS-CoV-2 in a school of 596 individuals. We estimate possible reductions in cases and hospitalizations among this population using a scenario-based analysis that accounts for (a) the risk of importation of infection from the community; (b) adherence to key Centers for Disease Control and Prevention-recommended mitigation strategies: mask wearing, cleaning and disinfection, hand hygiene, and social distancing; and (c) the effectiveness of contact tracing interventions at limiting onward transmission. RESULTS: Low impact and effectiveness of mitigation strategies (net effectiveness: 27%) result in approximately 40% of exposed staff and students becoming COVID-19 cases. When the net effectiveness of mitigation strategies was 69% or greater, in-school transmission was mostly prevented, yet importation of cases from the surrounding community could result in nearly 20% of the school's population becoming infected within 180 days. The combined effects of mitigation strategies and contact tracing were able to prevent most onward transmission. Hospitalizations were low among children and adults (<0.5% of the school population) across all scenarios examined. CONCLUSIONS: Based on our model, layering mitigation strategies and contact tracing can limit the number of cases that may occur from transmission in schools. Schools in communities with substantial levels of community spread will need to be more vigilant to ensure adherence of mitigation strategies to minimize transmission. Our results show that for school administrators, teachers, and parents to provide the safest environment, it is important to utilize multiple mitigation strategies and contract tracing that reduce SARS CoV-2 transmission by at least 69%. This will require training, reinforcement, and vigilance to ensure that the highest level of adherence is maintained over the entire school term.

The 20142016 West African outbreak of Ebola Virus Disease (EVD) was the largest and most deadly to date. Contact tracing, following up those who may have been infected through contact with an infected individual to prevent secondary spread, plays a vital role in controlling such outbreaks. Our aim in this work was to mechanistically represent the contact tracing process to illustrate potential areas of improvement in managing contact tracing efforts. We also explored the role contact tracing played in eventually ending the outbreak. We present a system of ordinary differential equations to model contact tracing in Sierra Leonne during the outbreak. Using data on cumulative cases and deaths, we estimate most of the parameters in our model. We include the novel features of counting the total number of people being traced and tying this directly to the number of tracers doing this work. Our work highlights the importance of incorporating changing behavior into ones model as needed when indicated by the data and reported trends. Our results show that a larger contact tracing program would have reduced the death toll of the outbreak. Counting the total number of people being traced and including changes in behavior in our model led to better understanding of disease management.

Emerging epidemics are challenging to track. Only a subset of cases is recognized and reported, as seen with the Zika virus (ZIKV) epidemic where large proportions of infection were asymptomatic. However, multiple imperfect indicators of infection provide an opportunity to estimate the underlying incidence of infection. We developed a modeling approach that integrates a generic Time-series Susceptible-Infected-Recovered epidemic model with assumptions about reporting biases in a Bayesian framework and applied it to the 2016 Zika epidemic in Puerto Rico using three indicators: suspected arboviral cases, suspected Zika-associated Guillain-Barré Syndrome cases, and blood bank data. Using this combination of surveillance data, we estimated the peak of the epidemic occurred during the week of August 15, 2016 (the 33rd week of year), and 120 to 140 (50% credible interval [CrI], 95% CrI: 97 to 170) weekly infections per 10,000 population occurred at the peak. By the end of 2016, we estimated that approximately 890,000 (95% CrI: 660,000 to 1,100,000) individuals were infected in 2016 (26%, 95% CrI: 19% to 33%, of the population infected). Utilizing multiple indicators offers the opportunity for real-time and retrospective situational awareness to support epidemic preparedness and response.

Preparation for outbreaks of emerging infectious diseases is often predicated on beliefs that we will be able to understand the epidemiological nature of an outbreak early into its inception. However, since many rare emerging diseases exhibit different epidemiological behaviors from outbreak to outbreak, early and accurate estimation of the epidemiological situation may not be straightforward in all cases. Previous studies have proposed considering the role of active asymptomatic infections co-emerging and co-circulating as part of the process of emergence of a novel pathogen. Thus far, consideration of the role of asymptomatic infections in emerging disease dynamics have usually avoided considering some important sets of influences. In this paper, we present and analyze a mathematical model to explore the hypothetical scenario that some (re)emerging diseases may actually be able to maintain stable, endemic circulation successfully in an entirely asymptomatic state. We argue that an understanding of this potential mechanism for diversity in observed epidemiological dynamics may be of considerable importance in understanding and preparing for outbreaks of novel and/or emerging diseases.

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.

Lack of maintenance on vacant neighborhood lots is associated with higher levels of depression, anxiety, and stress for nearby residents. Overgrown grasses and dense brush provide hiding spots for criminals and space to conduct illicit activities. This study builds upon previous research by investigating greening programs that engage community members to conduct routine maintenance on vacant lots within their neighborhoods. The Clean & Green program is a community-based solution that facilitates resident-driven routine maintenance of vacant lots in a midsized, Midwestern city. We use mixed effects regression to compare assault and violent crime counts on streets where vacant lot(s) are maintained by community members (N = 216) versus streets where vacant lots were left alone (N = 446) over a 5-year timeframe (2009-2013). Street segments with vacant lots maintained through the Clean & Green program had nearly 40% fewer assaults and violent crimes than street segments with vacant, abandoned lots, which held across 4 years with a large sample and efforts to test counterfactual explanations. Community-engaged greening programs may not only provide a solution to vacant lot maintenance, but also work as a crime prevention or reduction strategy. Engaging the community to maintain vacant lots in their neighborhood reduces costs and may increase the sustainability of the program.

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).

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.

Americans look to the Centers for Disease Control and Prevention (CDC) to lead by providing an example of healthy people in healthy environments. Recognizing the synergy between environmental health and personal health and well-being, the CDC formed the Go Green, Get Healthy (GGGH) initiative. The GGGH rolls healthier worksite initiatives, quality-of-work-life programs, and internal environmental protection efforts into a coordinated campaign for widespread cultural change with energy conservation as one of the major goals. The CDC hopes that this success will be a model for other agencies and organizations. The Office of Sustainability at the CDC actively engages the entire agency in environmental stewardship and specifically, energy conservation (in the GGGH initiative) by providing a vision with leadership support, education for every individual, effective communication methods, and a robust tracking system for comprehensive data and feedback. The campaign works effectively by breaking down the task of greening the agency into sectors. Each sector needs support of CDC leadership and work of responsible offices, complimented by the grassroots dedication of individuals in the GGGH workgroups and collaborative external partnerships. Several low/no-cost examples are included to demonstrate progress toward a sustainable CDC and these can be used to help other organizations discover a greener and healthier model for their sustainability and conservation efforts with a minimal outlay of funds. Through physical changes, culture changes, and policy/operational changes, energy and water can be saved. This paper seeks to convey the following main learning points: (1)identify low/no-cost ways to reduce energy and water consumption; (2)describe ways to influence workers to adopt more sustainable behaviors; and (3)discuss ways to integrate energy-management decision-making processes and standard operating procedures.