Redefining pandemic preparedness: Multidisciplinary insights from the CERP modelling workshop in infectious diseases, workshop report.

In July 2023, the Center of Excellence in Respiratory Pathogens organized a two-day workshop on infectious diseases modelling and the lessons learnt from the Covid-19 pandemic. This report summarizes the rich discussions that occurred during the workshop. The workshop participants discussed multisource data integration and highlighted the benefits of combining traditional surveillance with more novel data sources like mobility data, social media, and wastewater monitoring. Significant advancements were noted in the development of predictive models, with examples from various countries showcasing the use of machine learning and artificial intelligence in detecting and monitoring disease trends. The role of open collaboration between various stakeholders in modelling was stressed, advocating for the continuation of such partnerships beyond the pandemic. A major gap identified was the absence of a common international framework for data sharing, which is crucial for global pandemic preparedness. Overall, the workshop underscored the need for robust, adaptable modelling frameworks and the integration of different data sources and collaboration across sectors, as key elements in enhancing future pandemic response and preparedness.

Modelling disease mitigation at mass gatherings: A case study of COVID-19 at the 2022 FIFA World Cup.

The 2022 FIFA World Cup was the first major multi-continental sporting Mass Gathering Event (MGE) of the post COVID-19 era to allow foreign spectators. Such large-scale MGEs can potentially lead to outbreaks of infectious disease and contribute to the global dissemination of such pathogens. Here we adapt previous work and create a generalisable model framework for assessing the use of disease control strategies at such events, in terms of reducing infections and hospitalisations. This framework utilises a combination of meta-populations based on clusters of people and their vaccination status, Ordinary Differential Equation integration between fixed time events, and Latin Hypercube sampling. We use the FIFA 2022 World Cup as a case study for this framework (modelling each match as independent 7 day MGEs). Pre-travel screenings of visitors were found to have little effect in reducing COVID-19 infections and hospitalisations. With pre-match screenings of spectators and match staff being more effective. Rapid Antigen (RA) screenings 0.5 days before match day performed similarly to RT-PCR screenings 1.5 days before match day. Combinations of pre-travel and pre-match testing led to improvements. However, a policy of ensuring that all visitors had a COVID-19 vaccination (second or booster dose) within a few months before departure proved to be much more efficacious. The State of Qatar abandoned all COVID-19 related travel testing and vaccination requirements over the period of the World Cup. Our work suggests that the State of Qatar may have been correct in abandoning the pre-travel testing of visitors. However, there was a spike in COVID-19 cases and hospitalisations within Qatar over the World Cup. Given our findings and the spike in cases, we suggest a policy requiring visitors to have had a recent COVID-19 vaccination should have been in place to reduce cases and hospitalisations.

Development of an early alert model for pandemic situations in Germany.

The COVID-19 pandemic has pointed out the need for new technical approaches to increase the preparedness of healthcare systems. One important measure is to develop innovative early warning systems. Along those lines, we first compiled a corpus of relevant COVID-19 related symptoms with the help of a disease ontology, text mining and statistical analysis. Subsequently, we applied statistical and machine learning (ML) techniques to time series data of symptom related Google searches and tweets spanning the time period from March 2020 to June 2022. In conclusion, we found that a long-short-term memory (LSTM) jointly trained on COVID-19 symptoms related Google Trends and Twitter data was able to accurately forecast up-trends in classical surveillance data (confirmed cases and hospitalization rates) 14 days ahead. In both cases, F1 scores were above 98% and 97%, respectively, hence demonstrating the potential of using digital traces for building an early alert system for pandemics in Germany.

Preparing for the upcoming 2022/23 influenza season: A modelling study of the susceptible population in Australia, France, Germany, Italy, Spain and the United Kingdom.

We analysed the influenza epidemic that occurred in Australia during the 2022 winter using an age-structured dynamic transmission model, which accounts for past epidemics to estimate the population susceptibility to an influenza infection. We applied the same model to five European countries. Our analysis suggests Europe might experience an early and moderately large influenza epidemic. Also, differences may arise between countries, with Germany and Spain experiencing larger epidemics, than France, Italy and the United Kingdom, especially in children.

Modeling approaches for early warning and monitoring of pandemic situations as well as decision support.

The COVID-19 pandemic has highlighted the lack of preparedness of many healthcare systems against pandemic situations. In response, many population-level computational modeling approaches have been proposed for predicting outbreaks, spatiotemporally forecasting disease spread, and assessing as well as predicting the effectiveness of (non-) pharmaceutical interventions. However, in several countries, these modeling efforts have only limited impact on governmental decision-making so far. In light of this situation, the review aims to provide a critical review of existing modeling approaches and to discuss the potential for future developments.

Hospital admissions with influenza and impact of age and comorbidities on severe clinical outcomes in Brazil and Mexico.

BACKGROUND: The risk of hospitalization or death after influenza infection is higher at the extremes of age and in individuals with comorbidities. We estimated the number of hospitalizations with influenza and characterized the cumulative risk of comorbidities and age on severe outcomes in Mexico and Brazil. METHODS: We used national hospital discharge data from Brazil (SIH/SUS) from 2010-2018 and Mexico (SAEH) from 2010-2017 to estimate the number of influenza admissions using ICD-10 discharge codes, stratified by age (0-4, 5-17, 18-49, 50-64, and ≥65 years). Duration of hospital stay, admission to the intensive care unit (ICU), and in-hospital case fatality rates (CFRs) defined the severe outcomes. Rates were compared between patients with or without pre-specified comorbidities and by age. RESULTS: A total of 327,572 admissions with influenza were recorded in Brazil and 20,613 in Mexico, with peaks period most years. In Brazil, the median hospital stay duration was 3.0 days (interquartile range, 2.0-5.0), ICU admission rate was 3.3% (95% CI, 3.2-3.3%), and in-hospital CFR was 4.6% (95% CI, 4.5-4.7). In Mexico, the median duration of stay was 5.0 days (interquartile range, 3.0-7.0), ICU admission rate was 1.8% (95% CI, 1.6-2.0%), and in-hospital CFR was 6.9% (95% CI, 6.5-7.2). In Brazil, ICU admission and in-hospital CFR were higher in adults aged ≥50 years and increased in the presence of comorbidities, especially cardiovascular disease. In Mexico, comorbidities increased the risk of ICU admission by 1.9 (95% CI, 1.0-3.5) and in-hospital CFR by 13.9 (95% CI, 8.4-22.9) in children 0-4 years. CONCLUSION: The SIH/SUS and SAEH databases can be used to estimate hospital admissions with influenza, and the disease severity. Age and comorbidities, especially cardiovascular disease, are cumulatively associated with more severe outcomes, with differences between countries. This association should be further analyzed in prospective surveillance studies designed to support influenza vaccination strategy decisions.

Public health impact and cost-effectiveness of implementing a 'pre-vaccination screening' strategy with the dengue vaccine in Puerto Rico.

BACKGROUND: The World Health Organization (WHO) recommended 'pre-vaccination screening' as its preferred implementation strategy when using the licensed dengue vaccine (CYD-TDV; Dengvaxia, Sanofi), so that only individuals with previous dengue infection are vaccinated. The US Centers for Disease Control and Prevention (CDC) recommended use of CYD-TDV to prevent dengue in children with previous laboratory-confirmed dengue infection in regions where dengue is endemic. Here, we evaluate the public health impact and cost-effectiveness of a 'pre-vaccination screening' strategy in Puerto Rico. METHODS: The current analysis builds upon a previously published transmission model used to assess the benefits/risks associated with dengue vaccination. For 'pre-vaccination screening', three alternative testing methods were assessed: one using an immunoglobulin G (IgG) enzyme-linked immunosorbent assay (ELISA) dengue serotest, another with dengue serotesting using a rapid diagnostic test (RDT), and one using both sequentially (as recommended in Puerto Rico). The time horizon considered was 10 years. RESULTS: In Puerto Rico, the disability-adjusted life years (DALYs) averted for 'pre-vaccination screening' with an ELISA-based program, RDT-based program, and both sequentially would be a median 1,192 (95% CI: 716-2,232), 2,812 (95% CI: 1,579-5,019), and 1,017 (95% CI: 561-1,738), respectively. These benefits would arise from the reduction in cases: median 24,961 (95% CI: 17,480-36,782), 58,273 (95% CI: 40,729-84,796), 20,775 (95% CI: 14,637-30,374) fewer cases, respectively. The cost per DALY averted from a payer perspective would be US$12,518 (95 %CI: US$4,749-26,922), US$10,047 (95% CI: US$3,350-23,852), and US$12,334 (95% CI: US$4,965-26,444), respectively. All three strategies would be cost saving from a societal perspective. CONCLUSIONS: Our study supports the WHO and CDC 'pre-vaccination screening' guidance for CYD-TDV implementation. In Puerto Rico, regardless of the testing strategy and even with a relatively low rate of testing, it would be cost-effective from a payer perspective and cost saving from a societal perspective.

Estimating social contacts in mass gatherings for disease outbreak prevention and management: case of Hajj pilgrimage.

BACKGROUND: Most mass gathering events have been suspended due to the SARS-CoV-2 pandemic. However, with vaccination rollout, whether and how to organize some of these mass gathering events arises as part of the pandemic recovery discussions, and this calls for decision support tools. The Hajj, one of the world's largest religious gatherings, was substantively scaled down in 2020 and 2021 and it is still unclear how it will take place in 2022 and subsequent years. Simulating disease transmission dynamics during the Hajj season under different conditions can provide some insights for better decision-making. Most disease risk assessment models require data on the number and nature of possible close contacts between individuals. METHODS: We sought to use integrated agent-based modeling and discrete events simulation techniques to capture risky contacts among the pilgrims and assess different scenarios in one of the Hajj major sites, namely Masjid-Al-Haram. RESULTS: The simulation results showed that a plethora of risky contacts may occur during the rituals. Also, as the total number of pilgrims increases at each site, the number of risky contacts increases, and physical distancing measures may be challenging to maintain beyond a certain number of pilgrims in the site. CONCLUSIONS: This study presented a simulation tool that can be relevant for the risk assessment of a variety of (respiratory) infectious diseases, in addition to COVID-19 in the Hajj season. This tool can be expanded to include other contributing elements of disease transmission to quantify the risk of the mass gathering events.

Estimating dengue transmission intensity from serological data: A comparative analysis using mixture and catalytic models.

BACKGROUND: Dengue virus (DENV) infection is a global health concern of increasing magnitude. To target intervention strategies, accurate estimates of the force of infection (FOI) are necessary. Catalytic models have been widely used to estimate DENV FOI and rely on a binary classification of serostatus as seropositive or seronegative, according to pre-defined antibody thresholds. Previous work has demonstrated the use of thresholds can cause serostatus misclassification and biased estimates. In contrast, mixture models do not rely on thresholds and use the full distribution of antibody titres. To date, there has been limited application of mixture models to estimate DENV FOI. METHODS: We compare the application of mixture models and time-constant and time-varying catalytic models to simulated data and to serological data collected in Vietnam from 2004 to 2009 (N ≥ 2178) and Indonesia in 2014 (N = 3194). RESULTS: The simulation study showed larger mean FOI estimate bias from the time-constant and time-varying catalytic models (-0.007 (95% Confidence Interval (CI): -0.069, 0.029) and -0.006 (95% CI -0.095, 0.043)) than from the mixture model (0.001 (95% CI -0.036, 0.065)). Coverage of the true FOI was > 95% for estimates from both the time-varying catalytic and mixture model, however the latter had reduced uncertainty. When applied to real data from Vietnam, the mixture model frequently produced higher FOI and seroprevalence estimates than the catalytic models. CONCLUSIONS: Our results suggest mixture models represent valid, potentially less biased, alternatives to catalytic models, which could be particularly useful when estimating FOI from data with largely overlapping antibody titre distributions.

How did the adoption of wP-pentavalent affect the global paediatric vaccine coverage rate? A multicountry panel data analysis.

OBJECTIVES: Several studies have highlighted the effects of combination vaccines on immunisation coverage at the national or subnational level. This study examined the effects globally. Worldwide introduction of whole-cell pertussis pentavalent (wP-pentavalent) allowed estimation of incremental coverage effects of combination vaccines on the third doses of diphtheria, tetanus, pertussis (DTP3); hepatitis B (HepB3) and Haemophilus influenzae type B (Hib3). DESIGN: Multicountry panel data analysis. DATA SOURCES: Country-level vaccine coverage data of WHO/UNICEF for the years 1980-2018. METHODS: Linear mixed models were used to estimate the effects of wP-pentavalent introduction by incorporating proxy variables to control for time trend and other time-dependent changes in the immunisation programmes. RESULTS: Introduction of combination vaccines may have improved the coverage of DTP3 by 3percentage points(95% CI 2.5% to 3.6%) globally compared with the coverage in the pre-combination vaccine era. The comparison of coverage rates of HepB3 and Hib3 in before and after wP-pentavalent periods indicates that the introduction of combination vaccines improved the coverage by 10.1 percentage points (95% CI 8.4% to 11.7%) for HepB3 and 9.9 (95% CI 7.1% to 12.7%) for Hib3 in countries that introduced those antigens prior to adoption of wP-pentavalent. Even though the incremental coverage increase of DTP3 appears quite modest, it is still a significant result, especially because DTP vaccine has been in the national immunisation programmes of all countries for about 24 years prior to the introduction of wP-pentavalent. Additionally, the introduction of pentavalent also allowed inclusion of Hib and HepB in the vaccine schedule for a large number of countries (85 and 37, respectively, of the 102 countries included in our analysis). CONCLUSION: The findings suggest that development of combination vaccines with additional antigens is likely to help sustain and improve coverage of existing as well as new childhood vaccines.

Disease transmission and mass gatherings: a case study on meningococcal infection during Hajj.

BACKGROUND: Mass gatherings can not only trigger major outbreaks on-site but also facilitate global spread of infectious pathogens. Hajj is one of the largest mass gathering events worldwide where over two million pilgrims from all over the world gather annually creating intense congestion. METHODS: We developed a meta-population model to represent the transmission dynamics of Neisseria meningitidis and the impact of Hajj pilgrimage on the risk of invasive meningococcal disease (IMD) for pilgrims population, local population at the Hajj site and country of origin of Hajj pilgrims. This model was calibrated using data on IMD over 17 years (1995-2011) and further used to simulate potential changes in vaccine policy and endemic conditions. RESULTS: The effect of increased density of contacts during Hajj was estimated to generate a 78-fold increase in disease transmission that impacts not only pilgrims but also the local population. Quadrivalent ACWY vaccination was found to be very effective in reducing the risk of outbreak during Hajj. Hajj has more limited impact on IMD transmission and exportation in the pilgrim countries of origin, although not negligible given the size of the population considered. CONCLUSION: The analysis performed highlighted the amplifying effect of mass gathering on N. meningitidis transmission and confirm vaccination as a very effective preventive measure to mitigate outbreak risks.

Dengue Endemicity, Force of Infection, and Variation in Transmission Intensity in 13 Endemic Countries.

Dengue endemicity varies but comparative, multicountry data are extremely limited. An improved understanding is needed to prioritize prevention, including vaccination, which is currently recommended only under specific epidemiological conditions. We used serological study data from 46 geographical sites in 13 countries to estimate dengue force of infection (FOI, the proportion of children seroconverting per year) under assumptions of either age-constant or age-varying FOI, and the age at which 50% and 80% of children had been infected. After exclusions, 13 661 subjects were included. Estimated constant FOI varied widely, from 1.7% (Singapore) to 24.1% (the Philippines). In the site-level analysis 44 sites (96%) reached 50% seroconversion and 35 sites (75%) reached 80% seroconversion by age 18 years, with significant heterogeneity. These findings confirm that children living in dengue-endemic countries receive intense early dengue exposure, increasing risk of secondary infection, and imply serosurveys at fine spatial resolutions are needed to inform vaccination campaigns.

Large-scale frequent testing and tracing to supplement control of Covid-19 and vaccination rollout constrained by supply.

Non-pharmaceutical interventions (NPI) were implemented all around the world in the fight against COVID-19: Social distancing, shelter-in-place, mask wearing, etc. to mitigate transmission, together with testing and contact-tracing to identify, isolate and treat the infected. The majority of countries have relied on the former measures, followed by a ramping up of their testing and tracing capabilities. We present here the cases of South Korea, Italy, Canada and the United States, as a look back to lessons that can be drawn for controlling the pandemic, specifically through the means of testing and tracing. By fitting a disease transmission model to daily case report data in each of the four countries, we first show that their combination of social-distancing and testing/tracing have had a significant impact on the evolution of their first wave of pandemic curves. We then consider the hypothetical scenario where the only NPI measures implemented past the first pandemic wave consisted of isolating individuals due to repeated, country-scale testing and contact tracing, as a mean of lifting social distancing measures without a resurgence of COVID-19. We give estimates on the average isolation rates needed to occur in each country. We find that testing and tracing each individual of a country, on average, every 4.5 days (South Korea), 5.7 days (Canada), 6 days (Italy) and 3.5 days (US), would have been sufficient to mitigate their second pandemic waves. We also considered the situation in Canada to see how a frequent large-scale asymptomatic testing and contact tracing could have been used in combination with vaccination rollout to reduce the infection in the population. This could offer an alternative approach towards preventing and controlling an outbreak when vaccine supply is limited, while testing capacity has been increasingly enhanced.

Efficacy profile of the CYD-TDV dengue vaccine revealed by Bayesian survival analysis of individual-level phase III data.

Background: Sanofi-Pasteur's CYD-TDV is the only licensed dengue vaccine. Two phase three trials showed higher efficacy in seropositive than seronegative recipients. Hospital follow-up revealed increased hospitalisation in 2-5- year-old vaccinees, where serostatus and age effects were unresolved. Methods: We fit a survival model to individual-level data from both trials, including year 1 of hospital follow-up. We determine efficacy by age, serostatus, serotype and severity, and examine efficacy duration and vaccine action mechanism. Results: Our modelling indicates that vaccine-induced immunity is long-lived in seropositive recipients, and therefore that vaccinating seropositives gives higher protection than two natural infections. Long-term increased hospitalisation risk outweighs short-lived immunity in seronegatives. Independently of serostatus, transient immunity increases with age, and is highest against serotype 4. Benefit is higher in seropositives, and risk enhancement is greater in seronegatives, against hospitalised disease than against febrile disease. Conclusions: Our results support vaccinating seropositives only. Rapid diagnostic tests would enable viable 'screen-then-vaccinate' programs. Since CYD-TDV acts as a silent infection, long-term safety of other vaccine candidates must be closely monitored. Funding: Bill & Melinda Gates Foundation, National Institute for Health Research, UK Medical Research Council, Wellcome Trust, Royal Society. Clinical trial number: NCT01373281 and NCT01374516.

Mortality among Hospitalized Dengue Patients with Comorbidities in Mexico, Brazil, and Colombia.

Dengue patients with comorbidities may be at higher risk of death. In this cross-sectional study, healthcare databases from Mexico (2008-2014), Brazil (2008-2015), and Colombia (2009-2017) were used to identify hospitalized dengue cases and their comorbidities. Case fatality rates (CFRs), relative risk, and odds ratios (OR) for in-hospital mortality were determined. Overall, 678,836 hospitalized dengue cases were identified: 68,194 from Mexico, 532,821 from Brazil, and 77,821 from Colombia. Of these, 35%, 5%, and 18% were severe dengue, respectively. Severe dengue and age ≥ 46 years were associated with increased risk of in-hospital mortality. Comorbidities were identified in 8%, 1%, and 4% of cases in Mexico, Brazil, and Colombia, respectively. Comorbidities increased hospitalized dengue CFRs 3- to 17-fold; CFRs were higher with comorbidities regardless of dengue severity or age. The odds of in-hospital mortality were significantly higher in those with pulmonary disorders (11.6 [95% CI 7.4-18.2], 12.7 [95% CI 9.3-17.5], and 8.0 [95% CI 4.9-13.1] in Mexico, Brazil, and Colombia, respectively), ischemic heart disease (23.0 [95% CI 6.6-79.6], 5.9 [95% CI 1.4-24.6], and 7.0 [95% CI 1.9-25.5]), and renal disease/failure (8.3 [95% CI 4.8-14.2], 8.0 [95% CI 4.5-14.4], and 9.3 [95% CI 3.1-28.0]) across the three countries; the odds of in-hospital mortality from dengue with comorbidities was at least equivalent or higher than severe dengue alone (4.5 [95% CI 3.4-6.1], 9.6 [95% CI 8.6-10.6], and 9.0 [95% CI 6.8-12.0). In conclusion, the risk of death because of dengue increases with comorbidities independently of age and/or disease severity.

Potential impact of introducing vaccines against COVID-19 under supply and uptake constraints in France: A modelling study.

BACKGROUND: The accelerated vaccine development in response to the COVID-19 pandemic should lead to a vaccine being available early 2021, albeit in limited supply and possibly without full vaccine acceptance. We assessed the short-term impact of a COVID-19 immunization program with varying constraints on population health and non-pharmaceutical interventions (NPIs) needs. METHODS: A SARS-CoV-2 transmission model was calibrated to French epidemiological data. We defined several vaccine implementation scenarios starting in January 2021 based on timing of discontinuation of NPIs, supply and uptake constraints, and their relaxation. We assessed the number of COVID-19 hospitalizations averted, the need for and number of days with NPIs in place over the 2021-2022 period. RESULTS: An immunisation program under constraints could reduce the burden of COVID-19 hospitalizations by 9-40% if the vaccine prevents against infections. Relaxation of constraints not only reduces further COVID-19 hospitalizations (30-39% incremental reduction), it also allows for NPIs to be discontinued post-2021 (0 days with NPIs in 2022 versus 11 to 125 days for vaccination programs under constraints and 327 in the absence of vaccination). CONCLUSION: For 2021, COVID-19 control is expected to rely on a combination of NPIs and the outcome of early immunisation programs. The ability to overcome supply and uptake constraints will help prevent the need for further NPIs post-2021. As the programs expand, efficiency assessments will be needed to ensure optimisation of control policies post-emergency use.

Quantifying the annual incidence and underestimation of seasonal influenza: A modelling approach.

BACKGROUND: Seasonal influenza poses a significant public health and economic burden, associated with the outcome of infection and resulting complications. The true burden of the disease is difficult to capture due to the wide range of presentation, from asymptomatic cases to non-respiratory complications such as cardiovascular events, and its seasonal variability. An understanding of the magnitude of the true annual incidence of influenza is important to support prevention and control policy development and to evaluate the impact of preventative measures such as vaccination. METHODS: We use a dynamic disease transmission model, laboratory-confirmed influenza surveillance data, and randomized-controlled trial (RCT) data to quantify the underestimation factor, expansion factor, and symptomatic influenza illnesses in the US and Canada during the 2011-2012 and 2012-2013 influenza seasons. RESULTS: Based on 2 case definitions, we estimate between 0.42-3.2% and 0.33-1.2% of symptomatic influenza illnesses were laboratory-confirmed in Canada during the 2011-2012 and 2012-2013 seasons, respectively. In the US, we estimate between 0.08-0.61% and 0.07-0.33% of symptomatic influenza illnesses were laboratory-confirmed in the 2011-2012 and 2012-2013 seasons, respectively. We estimated the symptomatic influenza illnesses in Canada to be 0.32-2.4 million in 2011-2012 and 1.8-8.2 million in 2012-2013. In the US, we estimate the number of symptomatic influenza illnesses to be 4.4-34 million in 2011-2012 and 23-102 million in 2012-2013. CONCLUSIONS: We illustrate that monitoring a representative group within a population may aid in effectively modelling the transmission of infectious diseases such as influenza. In particular, the utilization of RCTs in models may enhance the accuracy of epidemiological parameter estimation.

The potential impact of dengue vaccination with, and without, pre-vaccination screening.

BACKGROUND: The World Health Organization defined a 'screen and vaccinate' strategy as its recommended policy for the licensed dengue vaccine (Dengvaxia, Sanofi Pasteur), so that only individuals with previous dengue infection are vaccinated. The objectives of the present study were to build upon a recently published analysis of the benefits and risks associated with dengue vaccination to evaluate the public health impact and cost-effectiveness of a screen and vaccinate strategy. METHODS: The current analysis was based on a previously reported transmission model and added, for the screening part, three rapid diagnostic tests with identical specificity (99%) but alternative sensitivities (50-70-90%) in the detection of prior dengue infection. The impact of a screen-and-vaccinate strategy considered nine settings representing different levels of transmission intensity. Outcomes (dengue-related hospitalizations, severe dengue, and symptomatic dengue) were assessed according to the level of transmission setting. The cost-effectiveness of vaccination in 10 endemic countries was also assessed. RESULTS: Although associated, in most cases, with a lower population impact than a 'no-screening' approach, a screen and vaccinate strategy is more effective in reducing the number of hospitalized and severe cases prevented per vaccination performed and generates positive health benefits for individuals screened and subsequently vaccinated. As a result, this intervention is cost-effective in all countries considered except for very low transmission settings. The overall population impact of a screen and vaccinate approach is also likely to be improved by the use of several rounds of screening (up to 48% reduction in dengue hospitalization over 10 years with 5 rounds). CONCLUSIONS: WHO recommended option of a screen and vaccinate policy is likely to have a positive impact both at the individual and population level across a wide range of transmission settings and has the potential to be as, if not more, cost-effective than a no screening strategy.

REAL-WORLD EVIDENCE OF DENGUE BURDEN ON HOSPITALS IN MEXICO: INSIGHTS FROM THE AUTOMATED SUBSYSTEM OF HOSPITAL DISCHARGES (SAEH) DATABASE.

BACKGROUND: The incidence of dengue in Mexico has increased in recent decades. It has been suggested that dengue outbreaks may compromise treatment quality in hospitals. OBJECTIVE: The objective of the study was to quantify the burden imposed by dengue on hospital services in Mexico. METHODS: We analyzed 19.2 million records contained in the database of hospital services of the Mexican Ministry of Health between 2008 and 2014. The number of admissions due to dengue was compared to other potentially preventable hospitalizations. Hospital departments were categorized to reflect dengue-related activity as high dengue activity (HDA), low dengue activity (LDA), or zero dengue activity departments, and the impact of dengue activity on general in-hospital mortality in HDA departments was assessed. RESULTS: Dengue was the cause of more hospital admissions than most of the potentially preventable prevalent acute and chronic conditions and other infectious diseases. In HDA departments, dengue patient load was found to be a significant risk factor for overall in-hospital mortality. There was an approximately two-fold higher dengue case-fatality rate in LDA versus HDA departments, irrespective of dengue severity. CONCLUSIONS: This study confirms that dengue is an important cause of hospitalization in Mexico and highlights the impact of dengue activity not only on dengue case-fatality rate but also on the overall in-hospital mortality.