Clinical evaluation of a web-based personalized recommendation system with electronic health record interface to optimize healthcare resources during SARS-CoV-2 surges.

During the SARS-CoV-2 pandemic, the German healthcare system faced challenges of efficiently allocating testing resources. To address this, we developed an open-source personalized recommendation system (PRS) called "CovApp". The PRS utilized a questionnaire to estimate the risk of infection, provided personalized recommendations such as testing, self-isolation, or quarantine, and featured QR code data transmission to electronic health records. The PRS served up to 2.5 million monthly users and received 67,000 backlinks from 1800 domains. We clinically evaluated the PRS at the SARS-CoV-2 testing facility at Charité and observed a 21.7% increase in patient throughput per hour and a 22.5% increase in patients per day. Patients using the PRS were twice as likely to belong to the High Risk group eligible for testing (18.6% vs. 8.9%, p < 0.0001), indicating successful compliance with CovApp's recommendations. CovApp served as a digital bridge between the population and medical staff and significantly improved testing efficiency. As an open-source platform, CovApp can be readily customized to address emerging public health crises. Further, given the EHR interface, the app is of great utility for other applications in clinical settings.

Toward a Common Performance and Effectiveness Terminology for Digital Proximity Tracing Applications.

Digital proximity tracing (DPT) for Sars-CoV-2 pandemic mitigation is a complex intervention with the primary goal to notify app users about possible risk exposures to infected persons. DPT not only relies on the technical functioning of the proximity tracing application and its backend server, but also on seamless integration of health system processes such as laboratory testing, communication of results (and their validation), generation of notification codes, manual contact tracing, and management of app-notified users. Policymakers and DPT operators need to know whether their system works as expected in terms of speed or yield (performance) and whether DPT is making an effective contribution to pandemic mitigation (also in comparison to and beyond established mitigation measures, particularly manual contact tracing). Thereby, performance and effectiveness are not to be confused. Not only are there conceptual differences but also diverse data requirements. For example, comparative effectiveness measures may require information generated outside the DPT system, e.g., from manual contact tracing. This article describes differences between performance and effectiveness measures and attempts to develop a terminology and classification system for DPT evaluation. We discuss key aspects for critical assessments of whether the integration of additional data measurements into DPT apps may facilitate understanding of performance and effectiveness of planned and deployed DPT apps. Therefore, the terminology and a classification system may offer some guidance to DPT system operators regarding which measurements to prioritize. DPT developers and operators may also make conscious decisions to integrate measures for epidemic monitoring but should be aware that this introduces a secondary purpose to DPT. Ultimately, the integration of further information (e.g., regarding exact exposure time) into DPT involves a trade-off between data granularity and linkage on the one hand, and privacy on the other. More data may lead to better epidemiological information but may also increase the privacy risks associated with the system, and thus decrease public DPT acceptance. Decision-makers should be aware of the trade-off and take it into account when planning and developing DPT systems or intending to assess the added value of DPT relative to the existing contact tracing systems.

Eliminating yellow fever epidemics in Africa: Vaccine demand forecast and impact modelling.

BACKGROUND: To counter the increasing global risk of Yellow fever (YF), the World Health Organisation initiated the Eliminate Yellow fever Epidemics (EYE) strategy. Estimating YF burden, as well as vaccine impact, while accounting for the features of urban YF transmission such as indirect benefits of vaccination, is key to informing this strategy. METHODS AND FINDINGS: We developed two model variants to estimate YF burden in sub-Saharan Africa, assuming all infections stem from either the sylvatic or the urban cycle of the disease. Both relied on an ecological niche model fitted to the local presence of any YF reported event in 34 African countries. We calibrated under-reporting using independent estimates of transmission intensity provided by 12 serological surveys performed in 11 countries. We calculated local numbers of YF infections, deaths and disability-adjusted life years (DALYs) lost based on estimated transmission intensity while accounting for time-varying vaccination coverage. We estimated vaccine demand and impact of future preventive mass vaccination campaigns (PMVCs) according to various vaccination scenarios. Vaccination activities conducted in Africa between 2005 and 2017 were estimated to prevent from 3.3 (95% CI 1.2-7.7) to 6.1 (95% CI 2.4-13.2) millions of deaths over the lifetime of vaccinees, representing extreme scenarios of none or maximal herd effects, respectively. By prioritizing provinces based on the risk of urban YF transmission in future PMVCs, an average of 37.7 million annual doses for PMVCs over eight years would avert an estimated 9,900,000 (95% CI 7,000,000-13,400,000) infections and 480,000 (180,000-1,140,000) deaths over the lifetime of vaccinees, corresponding to 1.7 (0.7-4.1) deaths averted per 1,000 vaccine doses. CONCLUSIONS: By estimating YF burden and vaccine impact over a range of spatial and temporal scales, while accounting for the specificity of urban transmission, our model can be used to inform the current EYE strategy.

POLICI: A web application for visualising and extracting yellow fever vaccination coverage in Africa.

Recent yellow fever (YF) outbreaks have highlighted the increasing global risk of urban spread of the disease. In context of recurrent vaccine shortages, preventive vaccination activities require accurate estimates of existing population-level immunity. We present POLICI (POpulation-Level Immunization Coverage - Imperial), an interactive online tool for visualising and extracting YF vaccination coverage estimates in Africa. We calculated single year age-disaggregated sub-national population-level vaccination coverage for 1950-2050 across the African endemic zone by collating vaccination information and inputting it into a demographic model. This was then implemented on an open interactive web platform. POLICI interactively displays age-disaggregated, population-level vaccination coverages at the first subnational administrative level, through numerous downloadable and customisable visualisations. POLICI is available at https://polici.shinyapps.io/yellow_fever_africa/. POLICI offers an accessible platform for relevant stakeholders in global health to access and explore vaccination coverages. These estimates have already been used to inform the WHO strategy to Eliminate Yellow fever Epidemics (EYE).

User Evaluation Indicates High Quality of the Surveillance Outbreak Response Management and Analysis System (SORMAS) After Field Deployment in Nigeria in 2015 and 2018.

During the West African Ebola virus disease outbreak in 2014-15, health agencies had severe challenges with case notification and contact tracing. To overcome these, we developed the Surveillance, Outbreak Response Management and Analysis System (SORMAS). The objective of this study was to measure perceived quality of SORMAS and its change over time. We ran a 4-week-pilot and 8-week-implementation of SORMAS among hospital informants in Kano state, Nigeria in 2015 and 2018 respectively. We carried out surveys after the pilot and implementation asking about usefulness and acceptability. We calculated the proportions of users per answer together with their 95% confidence intervals (CI) and compared whether the 2015 response distributions differed from those from 2018. Total of 31 and 74 hospital informants participated in the survey in 2015 and 2018, respectively. In 2018, 94% (CI: 89-100%) of users indicated that the tool was useful, 92% (CI: 86-98%) would recommend SORMAS to colleagues and 18% (CI: 10-28%) had login difficulties. In 2015, the proportions were 74% (CI: 59-90%), 90% (CI: 80-100%), and 87% (CI: 75-99%) respectively. Results indicate high usefulness and acceptability of SORMAS. We recommend mHealth tools to be evaluated to allow repeated measurements and comparisons between different versions and users.

Is there a duty to participate in digital epidemiology?

This paper poses the question of whether people have a duty to participate in digital epidemiology. While an implied duty to participate has been argued for in relation to biomedical research in general, digital epidemiology involves processing of non-medical, granular and proprietary data types that pose different risks to participants. We first describe traditional justifications for epidemiology that imply a duty to participate for the general public, which take account of the immediacy and plausibility of threats, and the identifiability of data. We then consider how these justifications translate to digital epidemiology, understood as an evolution of traditional epidemiology that includes personal and proprietary digital data alongside formal medical datasets. We consider the risks imposed by re-purposing such data for digital epidemiology and propose eight justificatory conditions that should be met in justifying a duty to participate for specific digital epidemiological studies. The conditions are then applied to three hypothetical cases involving usage of social media data for epidemiological purposes. We conclude with a list of questions to be considered in public negotiations of digital epidemiology, including the application of a duty to participate to third-party data controllers, and the important distinction between moral and legal obligations to participate in research.

Results from the first 12 months of the national surveillance of healthcare associated outbreaks in Germany, 2011/2012.

BACKGROUND: In August 2011, the German Protection against Infection Act was amended, mandating the reporting of healthcare associated infection (HAI) outbreak notifications by all healthcare workers in Germany via local public health authorities and federal states to the Robert Koch Institute (RKI). OBJECTIVE: To describe the reported HAI-outbreaks and the surveillance system's structure and capabilities. METHODS: Information on each outbreak was collected using standard paper forms and notified to RKI. Notifications were screened daily and regularly analysed. RESULTS: Between November 2011 and November 2012, 1,326 paper forms notified 578 HAI-outbreaks, between 7 and 116 outbreaks per month. The main causative agent was norovirus (n = 414/578; 72%). Among the 108 outbreaks caused by bacteria, the most frequent pathogens were Clostridium difficile (25%) Klebsiella spp. (19%) and Staphylococcus spp. (19%). Multidrug-resistant bacteria were responsible for 54/108 (50%) bacterial outbreaks. Hospitals were affected most frequently (485/578; 84%). Hospital outbreaks due to bacteria were mostly reported from intensive care units (ICUs) (45%), followed by internal medicine wards (16%). CONCLUSION: The mandatory HAI-outbreak surveillance system describes common outbreaks. Pathogens with a particular high potential to cause large or severe outbreaks may be identified, enabling us to further focus research and preventive measures. Increasing the sensitivity and reliability of the data collection further will facilitate identification of outbreaks able to increase in size and severity, and guide specific control measures to interrupt their propagation.

Vaccination coverage among children in Germany estimated by analysis of health insurance claims data.

In Germany, the national routine childhood immunization schedule comprises 12 vaccinations. Primary immunizations should be completed by 24 mo of age. However, nationwide monitoring of vaccination coverage (VC) is performed only at school entry. We utilized health insurance claims data covering ~85% of the total population with the objectives to (1) assess VC of all recommended childhood vaccinations in birth-cohorts 2004-2009, (2) analyze cross-sectional (at 24 and 36 mo) and longitudinal trends, and (3) validate the method internally and externally. Counting vaccine doses in a retrospective cohort fashion, we assembled individual vaccination histories and summarized VC to nationwide figures. For most long-established vaccinations, VC at 24 mo was at moderate levels (~73-80%) and increased slightly across birth-cohorts. One dose measles VC was high (94%), but low (69%) for the second dose. VC with a full course of recently introduced varicella, pneumococcal, and meningococcal C vaccines increased across birth-cohorts from below 10% above 60%, 70%, and 80%, respectively. At 36 mo, VC had increased further by up to 15 percentage points depending on vaccination. Longitudinal analysis suggested a continued VC increase until school entry. Validation of VC figures with primary data showed an overall good agreement. In conclusion, analysis of health insurance claims data allows for the estimation of VC among children in Germany considering completeness and timeliness of vaccination series. This approach provides valid nationwide VC figures for all currently recommended pediatric vaccinations and fills the information gap between early infancy and late assessment at school entry.

MRSA transmission on a neonatal intensive care unit: epidemiological and genome-based phylogenetic analyses.

BACKGROUND: Methicillin-resistant Staphylococcus aureus (MRSA) may cause prolonged outbreaks of infections in neonatal intensive care units (NICUs). While the specific factors favouring MRSA spread on neonatal wards are not well understood, colonized infants, their relatives, or health-care workers may all be sources for MRSA transmission. Whole-genome sequencing may provide a new tool for elucidating transmission pathways of MRSA at a local scale. METHODS AND FINDINGS: We applied whole-genome sequencing to trace MRSA spread in a NICU and performed a case-control study to identify risk factors for MRSA transmission. MRSA genomes had accumulated sequence variation sufficiently fast to reflect epidemiological linkage among individual patients, between infants and their mothers, and between infants and staff members, such that the relevance of individual nurses' nasal MRSA colonization for prolonged transmission could be evaluated. In addition to confirming previously reported risk factors, we identified an increased risk of transmission from infants with as yet unknown MRSA colonisation, in contrast to known MRSA-positive infants. CONCLUSIONS: The integration of epidemiological (temporal, spatial) and genomic data enabled the phylogenetic testing of several hypotheses on specific MRSA transmission routes within a neonatal intensive-care unit. The pronounced risk of transmission emanating from undetected MRSA carriers suggested that increasing the frequency or speed of microbiological diagnostics could help to reduce transmission of MRSA.

The FIFA Women's World Cup in Germany 2011--a practical example for tailoring an event-specific enhanced infectious disease surveillance system.

BACKGROUND: Mass gatherings require a decision from public health authorities on how to monitor infectious diseases during the event. The appropriate level of enhanced surveillance depends on parameters like the scale of the event (duration, spatial distribution, season), participants' origin, amount of public attention, and baseline disease activity in the host country. For the FIFA Men's World Cup 2006, Germany implemented enhanced surveillance. As the scale of the FIFA Women's World Cup (June 26 - July 17, 2011) was estimated to be substantially smaller in size, visitors and duration, it was not feasible to simply adopt the previously implemented measures. Our aim was therefore to develop a strategy to tailor an event-specific enhanced surveillance for this smaller-scale mass gathering. METHODS: Based on the enhanced surveillance measures during the Men's Cup, we conducted a needs assessment with the district health authorities in the 9 host cities in March 2011. Specific measures with a majority consent were implemented. After the event, we surveyed the 9 district and their corresponding 7 state health authorities to evaluate the implemented measures. RESULTS: All 9 district health authorities participated in the pre-event needs assessment. The majority of sites consented to moving from weekly to daily (Monday-Friday) notification reporting of routine infectious diseases, receiving regular feedback on those notification reports and summaries of national/international World Cup-relevant epidemiological incidents, e.g. outbreaks in countries of participating teams. In addition, we decided to implement twice-weekly reports of "unusual events" at district and state level. This enhanced system would commence on the first day and continue to one day following the tournament. No World Cup-related infectious disease outbreaks were reported during this time period. Eight of 9 district and 6 of 8 state health authorities participated in the final evaluation. The majority perceived the implemented measures as adequate. CONCLUSIONS: Our approach to tailor an event-specific enhanced surveillance concept worked well. Involvement of the participating stakeholders early-on in the planning phase secured ownership of and guaranteed support for the chosen strategy. The enhanced surveillance for this event resulted as a low-level surveillance. However, we included mechanisms for rapid upscaling if the situation would require adaptations.

Climate-based models for understanding and forecasting dengue epidemics.

BACKGROUND: Dengue dynamics are driven by complex interactions between human-hosts, mosquito-vectors and viruses that are influenced by environmental and climatic factors. The objectives of this study were to analyze and model the relationships between climate, Aedes aegypti vectors and dengue outbreaks in Noumea (New Caledonia), and to provide an early warning system. METHODOLOGY/PRINCIPAL FINDINGS: Epidemiological and meteorological data were analyzed from 1971 to 2010 in Noumea. Entomological surveillance indices were available from March 2000 to December 2009. During epidemic years, the distribution of dengue cases was highly seasonal. The epidemic peak (March-April) lagged the warmest temperature by 1-2 months and was in phase with maximum precipitations, relative humidity and entomological indices. Significant inter-annual correlations were observed between the risk of outbreak and summertime temperature, precipitations or relative humidity but not ENSO. Climate-based multivariate non-linear models were developed to estimate the yearly risk of dengue outbreak in Noumea. The best explicative meteorological variables were the number of days with maximal temperature exceeding 32°C during January-February-March and the number of days with maximal relative humidity exceeding 95% during January. The best predictive variables were the maximal temperature in December and maximal relative humidity during October-November-December of the previous year. For a probability of dengue outbreak above 65% in leave-one-out cross validation, the explicative model predicted 94% of the epidemic years and 79% of the non epidemic years, and the predictive model 79% and 65%, respectively. CONCLUSIONS/SIGNIFICANCE: The epidemic dynamics of dengue in Noumea were essentially driven by climate during the last forty years. Specific conditions based on maximal temperature and relative humidity thresholds were determinant in outbreaks occurrence. Their persistence was also crucial. An operational model that will enable health authorities to anticipate the outbreak risk was successfully developed. Similar models may be developed to improve dengue management in other countries.

Timeliness of surveillance during outbreak of Shiga Toxin-producing Escherichia coli infection, Germany, 2011.

In the context of a large outbreak of Shiga toxin-producing Escherichia coli O104:H4 in Germany, we quantified the timeliness of the German surveillance system for hemolytic uremic syndrome and Shiga toxin-producing E. coli notifiable diseases during 2003-2011. Although reporting occurred faster than required by law, potential for improvement exists at all levels of the information chain.

Survey on the population's needs and the public health response during floods in Germany 2002.

A survey after the 2002 flood in Germany identifies contact with floodwater as a risk factor for diarrhea and injuries and shows that the affected population valued the given professional support in securing homes and cleanup work. Evacuations were well tolerated. Information reached the population mainly through loudspeakers, radio, and TV.

SurvNet electronic surveillance system for infectious disease outbreaks, Germany.

In 2001, the Robert Koch Institute (RKI) implemented a new electronic surveillance system (SurvNet) for infectious disease outbreaks in Germany. SurvNet has captured 30,578 outbreak reports in 2001-2005. The size of the outbreaks ranged from 2 to 527 cases. For outbreaks reported in 2002-2005, the median duration from notification of the first case to the local health department until receipt of the outbreak report at RKI was 7 days. Median outbreak duration ranged from 1 day (caused by Campylobacter) up to 73 days (caused by Mycobacterium tuberculosis). The most common settings among the 10,008 entries for 9,946 outbreaks in 2004 and 2005 were households (5,262; 53%), nursing homes (1,218; 12%), and hospitals (1,248; 12%). SurvNet may be a useful tool for other outbreak surveillance systems because it minimizes the workload of local health departments and captures outbreaks even when causative pathogens have not yet been identified.

Reliability of case definitions for public health surveillance assessed by Round-Robin test methodology.

BACKGROUND: Case definitions have been recognized to be important elements of public health surveillance systems. They are to assure comparability and consistency of surveillance data and have crucial impact on the sensitivity and the positive predictive value of a surveillance system. The reliability of case definitions has rarely been investigated systematically. METHODS: We conducted a Round-Robin test by asking all 425 local health departments (LHD) and the 16 state health departments (SHD) in Germany to classify a selection of 68 case examples using case definitions. By multivariate analysis we investigated factors linked to classification agreement with a gold standard, which was defined by an expert panel. RESULTS: A total of 7870 classifications were done by 396 LHD (93%) and all SHD. Reporting sensitivity was 90.0%, positive predictive value 76.6%. Polio case examples had the lowest reporting precision, salmonellosis case examples the highest (OR = 0.008; CI: 0.005-0.013). Case definitions with a check-list format of clinical criteria resulted in higher reporting precision than case definitions with a narrative description (OR = 3.08; CI: 2.47-3.83). Reporting precision was higher among SHD compared to LHD (OR = 1.52; CI: 1.14-2.02). CONCLUSION: Our findings led to a systematic revision of the German case definitions and build the basis for general recommendations for the creation of case definitions. These include, among others, that testable yes/no criteria in a check-list format is likely to improve reliability, and that software used for data transmission should be designed in strict accordance with the case definitions. The findings of this study are largely applicable to case definitions in many other countries or international networks as they share the same structural and editorial characteristics of the case definitions evaluated in this study before their revision.

Respiratory disease caused by a species B2 adenovirus in a military camp in Turkey.

In April 2004, two patients were admitted to hospital in Berlin, Germany, with clinical signs of acute respiratory infection after returning from a military exercise in their home country of Turkey. They were admitted to a high security infectious disease unit as epidemiological data pointed to an outbreak of unknown etiology. Samples taken at the time of admission proved to be strongly positive for Adenovirus by PCR, but negative for Influenza A/H1N1 virus, Influenza A/H3N2 virus, Influenza B virus, Respiratory syncytial virus, and SARS coronavirus. No evidence for bacterial infection was obtained by serological tests and blood cultures. The adenovirus detected was characterized further by genotyping and was identified as a species B2 virus with the highest similarity to adenovirus type 11a.

Toward a Unified Timestamp with explicit precision.

Demographic and health surveillance (DS) systems monitor and document individual and group-level processes in well-defined populations over long periods of time. The resulting data are complex and inherently temporal. Established methods of storing and manipulating temporal data are unable to adequately address the challenges posed by these data. Building on existing standards, a temporal framework and notation are presented that are able to faithfully record all of the time-related information (or partial lack thereof) produced by surveillance systems. The Unified Timestamp isolates all of the inherent complexity of temporal data into a single data type and provides the foundation on which a Unified Timestamp class can be built. The Unified Timestamp accommodates both point- and interval-based time measures with arbitrary precision, including temporal sets. Arbitrary granularities and calendars are supported, and the Unified Timestamp is hierarchically organized, allowing it to represent an unlimited array of temporal entities.