Machine learning mathematical models for incidence estimation during pandemics.

Accurate estimates of the incidence of infectious diseases are key for the control of epidemics. However, healthcare systems are often unable to test the population exhaustively, especially when asymptomatic and paucisymptomatic cases are widespread; this leads to significant and systematic under-reporting of the real incidence. Here, we propose a machine learning approach to estimate the incidence of a pandemic in real-time, using reported cases and the overall test rate.

in Wild Lagomorphs in Southern Spain's Mediterranean Ecosystems.

is a vector-borne zoonotic bacterium that causes tularemia, a disease of great importance for animal and public health. Although wild lagomorphs are considered one of the major reservoirs of this bacterium, information about the circulation of in European wild rabbit () and Iberian hare () populations in Europe is still very limited. In Spain, is present in northern central regions, with recurrent outbreaks occurring annually.

Cost minimization analysis of treatments for metastatic HER2-positive breast cancer in Peru: Fixed-dose combination of pertuzumab and trastuzumab for subcutaneous injections.

The main objective of this study is to determine whether the employment of fixed-dose combination of pertuzumab and trastuzumab for subcutaneous injection (PH FDC SC; and Phesgo as brand name) to treat metastatic HER2-positive breast cancer patients would minimize costs compared to the traditional treatment of separate intravenous doses of pertuzumab and trastuzumab in Peru. To achieve this, we used EsSalud (the social security health insurance) data and assessed it through a mixed strategy, which consisted of a quantitative and a qualitative approach. The first one aimed to calculate the direct (non-drug consumables, drugs, and healthcare professionals) and indirect costs of both treatments to develop a comparison, whilst the second aimed to validate information and internalize the procedure in an EsSalud context.

A social norms campaign based positive intervention aimed at promoting protective behaviours.

Introduction: Social norms campaigns are communication strategies designed to influence people's behaviour by highlighting the social norms of their reference group. Such campaigns have been shown to be effective in promoting healthy behaviours in a variety of settings. This study explored the effectiveness of a social norms campaign applied to COVID-19 protective behaviours among university students during the pandemic.

Exploring spatial segregation induced by competition avoidance as driving mechanism for emergent coexistence in microbial communities.

This study investigates the role of spatial segregation, prompted by competition avoidance, as a key mechanism for emergent coexistence within microbial communities. Recognizing these communities as complex adaptive systems, we challenge the sufficiency of mean-field pairwise interaction models, and we consider the impact of spatial dynamics. We developed an individual-based spatial simulation depicting bacterial movement through a pattern of random walks influenced by competition avoidance, leading to the formation of spatially segregated clusters.