The challenges of open data for future epidemic preparedness: The experience of the 2022 Ebolavirus outbreak in Uganda.

On 20 September 2022, the Ministry of Health in Uganda, together with the World Health Organization-Regional Office for Africa (WHO AFRO) confirmed an outbreak of EVD due to Sudan ebolavirus in Mubende District, after one fatal case was confirmed. Real-time information are needed to provide crucial information to understand transmissibility, risk of geographical spread, routes of transmission, risk factors of infection, and provide the basis for epidemiological modelling that can inform response and containment planning to reduce the burden of disease. We made an effort to build a centralized repository of the Ebola virus cases from verified sources, providing information on dates of symptom onset, locations (aggregated to the district level), and when available, the gender and status of hospitals, reporting bed capacity and isolation unit occupancy rate according to the severity status of the patient. The proposed data repository provides researchers and policymakers timely, complete, and easy-accessible data to monitor the most recent trends of the Ebola outbreak in Ugandan districts with informative graphical outputs. This favors a rapid global response to the disease, enabling governments to prioritize and adjust their decisions quickly and effectively in response to the rapidly evolving emergency, with a solid data basis.

Monkeypox: Early estimation of basic reproduction number R0 in Europe.

This world outbreak of Monkeypox (MPX) infections outside Africa emerged on May 2022 in Europe and spread worldwide with unique characteristics: inter-human contagion and infection in men without specific previous immunization, prevalently men-who-have-sex-with-men (MSM). Phylogenetic analysis confirmed a unique clade, the West African clade, subclade IIb. On August 30, WHO stated 48 895 laboratory confirmed cases from 101 different countries, of which 28 050 were in Europe. It has therefore become important to define new epidemiological indices. Starting from our new surveillance system EpiMPX open data, we defined an early R0 measure, using European ECDC confirmed cases from the epidemic start to the end of August 2022; our early R0 pooled median is 2.44, with high variability between countries. We observed the higher R0 in Portugal and Germany, followed by Italy, Spain, and France. Anyway, these high estimates refer to the MSM group rather than to the general population. Early estimation of R0 can be used to support the epidemiological understanding of transmission dynamics and contain MPX from spreading in naive populations and core groups with risk factors. MPX is in an evolving situation with much to learn and to do to combat the current epidemic outbreak.

Trends and Spatiotemporal Patterns of Avian Influenza Outbreaks in Italy: A Data-Driven Approach.

In recent years, the unprecedented spread of the Avian Influenza Viruses (AIVs) among birds and mammals has caused devastation in animal populations, including poultry, wild birds, and some mammals, damaging farmers' livelihoods and the food trade. Given the urgency of the situation, it is particularly important that scientists and the public can access research results and data as soon as possible. The main aim of this study is to present a global open-access dataset of Avian Influenza outbreaks to enable researchers and policymakers (i) to rapidly detect, and respond to animal outbreaks as the first line of defense; (ii) to conduct epidemiological and virological investigations around animal outbreaks and human infections; and (iii) to communicate the risk. We show the potential use of this dataset to the research community by analyzing the most updated information on past and current Highly Pathogenic Avian Influenza (HPAI) outbreaks in domestic poultry and wild birds over the period from October 2021 to July 2023 in Italy. In addition, we applied indices borrowed from Economics (such as Homogeneity, Specialization, and Location Index) to the wild birds dataset to show their possible usage in epidemiology.

Monkeypox: EpiMPX Surveillance System and Open Data with a Special Focus on European and Italian Epidemic.

Background: The current out-of-Africa 2022 outbreak of Monkeypox requires a coordinated, international response through the rapid sharing of data and research results, as we have seen with COVID-19 and the previous Ebola and Zika outbreaks, which demonstrated how important real-world data are to inform public health, to create surveillance systems, to determine policy decisions and to improve clinical trials. Objectives: To support global response efforts by providing public access to real-time Monkeypox-related data for effective use of open data that could accelerate scientific knowledge and discoveries in terms of understanding, preventing, and treating the disease. In practice, to create a new surveillance system easy to consult and utilize. Study design: This work aims to build a surveillance system, namely EpiMPX, that allows researchers and policymakers to monitor the impact of Monkeypox in Europe, with a special focus on the epidemic trends in the Italian regions, based on an open-access database containing information on the laboratory confirmed Monkeypox cases reported by EU/EEA countries and updated once a week. In addition, users will be provided open-access R codes to estimate key epidemiological parameters such as the reproduction number (updating the Serial Interval distribution when new estimates will be published) and produce real-time results on their devices. Results: EpiMPX monitors the space-time distribution of cases and their characteristics, such as age, gender, symptoms, clinical status, and sexual orientation, when available. Even if it is currently too early for reliable calculation of epidemiological parameters, we estimated reproduction number R t in European countries with more than 28 days of observed incidence, assuming that the Serial Interval (SI) early estimate in Italy is valid for other countries too. This provides a direct visual assessment of the geographic distribution of risk areas as well as insights into the evolution of the outbreak over time. Italian data were evaluated concerning gender, region prevalence and cumulative data. Conclusions: The proposed EpiMPX surveillance system provides an overview of the European and Italian Monkeypox epidemiological situation with an open-access database to support epidemiological understanding of the origins and transmission dynamics of the disease with informative graphical outputs. These data confirmed the prevalent expression of Monkeypox within males, both in Europe and Italy. European MSM patients were affected by Monkeypox in a high percentage, confirming close sexual contact and possible sexual transmission. For the first time, Italian data on the regional distribution of cases and gender distribution were graphically evaluated. The data and research results are freely available and can be easily enriched to provide a prompt response to the scientific community and accelerate global efforts to contain the Monkeypox virus.

Hepatitis of unknown origin in children: Why and how to create an open access database.

During the early stages of an epidemic, obtaining reliable data is a challenge, especially on a global scale. The COVID-19 pandemic has underlined the importance of having "open data" (i.e., data which are made accessible and available in a standardized machine-readable format and under a license that allows it to be re-used and reshared) to inform health policy decisions and improve clinical trials. The main goal of our work is to provide effective, timely and comprehensive data to investigate this emerging virus, i.e., the acute hepatitis of unknown origin in children. These data can be used: 1) to conduct real-time situation analysis, and early and timely diagnosis for effective containment; 2) to facilitate coordination and collaboration between national and local governments; 3) to inform citizens on the spread of the disease in the world; and 4) to support governments in the future prevention decisions.

Predicting the Spread of SARS-CoV-2 in Italian Regions: The Calabria Case Study, February 2020-March 2022.

Despite the stunning speed with which highly effective and safe vaccines have been developed, the emergence of new variants of SARS-CoV-2 causes high rates of (re)infection, a major impact on health care services, and a slowdown to the socio-economic system. For COVID-19, accurate and timely forecasts are therefore essential to provide the opportunity to rapidly identify risk areas affected by the pandemic, reallocate the use of health resources, design countermeasures, and increase public awareness. This paper presents the design and implementation of an approach based on autoregressive models to reliably forecast the spread of COVID-19 in Italian regions. Starting from the database of the Italian Civil Protection Department (DPC), the experimental evaluation was performed on real-world data collected from February 2020 to March 2022, focusing on Calabria, a region of Southern Italy. This evaluation shows that the proposed approach achieves a good predictive power for out-of-sample predictions within one week (R-squared > 0.9 at 1 day, R-squared > 0.7 at 7 days), although it decreases with increasing forecasted days (R-squared > 0.5 at 14 days).