Spatiotemporal and meteorological relationships in dengue transmission in the Dominican Republic, 2015-2019.

Dengue has broadened its global distribution substantially in the past two decades, and many endemic areas are experiencing increases in incidence. The Dominican Republic recently experienced its two largest outbreaks to date with 16,836 reported cases in 2015 and 20,123 reported cases in 2019. With continued increases in dengue transmission, developing tools to better prepare healthcare systems and mosquito control agencies is of critical importance. Before such tools can be developed, however, we must first better understand potential drivers of dengue transmission. To that end, we focus in this paper on determining relationships between climate variables and dengue transmission with an emphasis on eight provinces and the capital city of the Dominican Republic in the period 2015-2019. We present summary statistics for dengue cases, temperature, precipitation, and relative humidity in this period, and we conduct an analysis of correlated lags between climate variables and dengue cases as well as correlated lags among dengue cases in each of the nine locations. We find that the southwestern province of Barahona had the largest dengue incidence in both 2015 and 2019. Among all climate variables considered, lags between relative humidity variables and dengue cases were the most frequently correlated. We found that most locations had significant correlations with cases in other locations at lags of zero weeks. These results can be used to improve predictive models of dengue transmission in the country.

Epidemic Diffusion Network of Spain: A Mobility Model to Characterize the Transmission Routes of Disease.

Human mobility drives the geographical diffusion of infectious diseases at different scales, but few studies focus on mobility itself. Using publicly available data from Spain, we define a Mobility Matrix that captures constant flows between provinces by using a distance-like measure of effective distance to build a network model with the 52 provinces and 135 relevant edges. Madrid, Valladolid and Araba/Álaba are the most relevant nodes in terms of degree and strength. The shortest routes (most likely path between two points) between all provinces are calculated. A total of 7 mobility communities were found with a modularity of 63%, and a relationship was established with a cumulative incidence of COVID-19 in 14 days (CI14) during the study period. In conclusion, mobility patterns in Spain are governed by a small number of high-flow connections that remain constant in time and seem unaffected by seasonality or restrictions. Most of the travels happen within communities that do not completely represent political borders, and a wave-like spreading pattern with occasional long-distance jumps (small-world properties) can be identified. This information can be incorporated into preparedness and response plans targeting locations that are at risk of contagion preventively, underscoring the importance of coordination between administrations when addressing health emergencies.

Understanding the use of evidence in the WHO Classification of Tumours: a protocol for an evidence gap map of the classification of tumours of the lung.

INTRODUCTION: There are gaps in the evidence base of tumour classification despite being essential for cancer diagnosis, treatment and patient care. The WHO in charge of the production of an updated international classification, the WHO Classification of Tumours (WCT), aims to adapt evidence gap map (EGM) methodology to inform future editions of the WCT, by providing a visual summary of the existing evidence. METHODS AND ANALYSIS: Bibliographical references used in the WCT fifth edition of Tumours of the Lung (Thoracic Tumours volume) will be used as search results of a literature search. A descriptive analysis of the cited evidence for tumour types and descriptors will be drafted and plotted in EPPI-Reviewer to develop a visual evidence map. The resulting EGM will reflect the number of cited studies in the size of the spheres, and the level of evidence by applying a four-colour code (red=low level evidence, orange=moderate level, green=high level and blue=unclassifiable). Overview of the findings will be provided in narrative form and a report will discuss the overall stage of cited research in the WCT and will include analysis of gaps, under-researched categories of tumour descriptors and pockets of low-level evidence. ETHICS AND DISSEMINATION: No ethics approval will be required as this is a study of previously published material. Findings of the EGM will be published and used to guide editors, stakeholders and researchers for future research planning and related decision-making, especially for the development of future editions of the WCT. PROSPERO REGISTRATION NUMBER: CRD42022302327.

Secondary Attack Rate, Transmission and Incubation Periods, and Serial Interval of SARS-CoV-2 Omicron Variant, Spain.

Contact tracing data of SARS-CoV-2 Omicron variant cases during December 2021 in Cantabria, Spain, showed increased transmission (secondary attack rate 39%) compared with Delta cases (secondary attack rate 26%), uninfluenced by vaccination status. Incubation and serial interval periods were also reduced. Half of Omicron transmissions happened before symptom onset in the index case-patient.

Real time surveillance of COVID-19 space and time clusters during the summer 2020 in Spain.

BACKGROUND: On June 21st de-escalation measures and state-of-alarm ended in Spain after the COVID-19 first wave. New surveillance and control strategy was set up to detect emerging outbreaks. AIM: To detect and describe the evolution of COVID-19 clusters and cases during the 2020 summer in Spain. METHODS: A near-real time surveillance system to detect active clusters of COVID-19 was developed based on Kulldorf's prospective space-time scan statistic (STSS) to detect daily emerging active clusters. RESULTS: Analyses were performed daily during the summer 2020 (June 21st - August 31st) in Spain, showing an increase of active clusters and municipalities affected. Spread happened in the study period from a few, low-cases, regional-located clusters in June to a nationwide distribution of bigger clusters encompassing a higher average number of municipalities and total cases by end-August. CONCLUSION: STSS-based surveillance of COVID-19 can be of utility in a low-incidence scenario to help tackle emerging outbreaks that could potentially drive a widespread transmission. If that happens, spatial trends and disease distribution can be followed with this method. Finally, cluster aggregation in space and time, as observed in our results, could suggest the occurrence of community transmission.