Purpose – This paper aims to contribute towards a better understanding of the partner selection process, which anticipates a successful co-opetition partnership. Co-opetition partnerships refer to developing cooperation efforts between competitors. The scarcity of studies conducted in this field to date provides limited contribution for the understanding of the partner selection process in this, particularly, paradoxical concept. Design/methodology/approach – This study follows a methodology based on systematic combining for the qualitative analysis of four cases of domestic co-opetition in Portugal. A sample range of eight companies was selected for a series of semi-structured interviews. Testimonials were transcribed and data coded for content analysis. Findings – Results indicate that prior personal relationships between decision-makers are facilitators for the implementation of cooperation partnerships with competitors. Based on these findings, this paper proposes a three-step model to explain the process of partner selection for co-opetition partnerships. According to this model, after opting to commence a new coopetitive business alliance, the manager undergoes a first unconscious selection based on his/her own prior personal relationships, followed by a conscious and judicious selection based on specific criteria related to partner’s operational skills, resources, effectiveness and trust. Research limitations/implications – Given that the sample is entirely formed by companies from one single country, further research would benefit from the inclusion of other countries expressing different business contexts and cultural environments. Originality/value – The value of paper derives from the comprehensive realization of partner selection for domestic co-opetition as fundamentally a network-related process.

No abstract

The close contact between patients and community pharmacists, along with the extensive geographical distribution of pharmacies in Portugal, offer exceptional conditions to detect and report adverse drug reactions (ADR). This study aimed to evaluate the motivation and knowledge of spontaneous reporting of ADR by community pharmacists of Porto, Portugal. Secondly, we aimed to generate real-world evidence on the main factors determining ADR report and at raising potential alternatives to the current reporting procedure in community pharmacy. We performed a descriptive, cross-sectional, observational, anonymous web survey-based study. Between April and July 2021, a web survey was implemented, targeting community pharmacists in the Porto district, Portugal. We validated 217 surveys from pharmacists. Regular notifiers seem to be more familiarised than non-regular notifiers with the Portuguese Pharmacovigilance System (PPS), with the Portal RAM for reporting suspected ADR, and with the update of the concept of ADR. Moreover, regular notifiers seem to be more proactive with their care in questioning patients about ADR and have more self-knowledge to identify suspected ADR. Conversely, non-regular notifiers, seem to be more reluctant to be judged by their ADR reporting activities. Respondents suggested to simplify and optimise the reporting process (31% of the suggestions), or to integrate a reporting platform into the pharmacy’s software (27%). This study identified opportunities to promote the ADR reporting process by community pharmacists, namely receiving feedback from the PPS on the reported case and its regulatory implications, implementing training programs in pharmacovigilance, and creating solutions to simplify the reporting process.

IntroductionThe rapid evolution of the therapeutic landscape in oncology poses challenges to optimal treatment sequencing. Evidence for clinical decision-making is often limited to studies focused on treatment evaluation at a single decision point, with limited capability of identifying delayed effects of prior treatment decisions on the efficacy and feasibility of future treatments. There is a growing interest in dynamic treatment regimes (DTRs) evaluation as it provides guidance on treatment individualisation based on evolving treatment and patient characteristics. In this scoping review we aim to systematically map how and to what extent DTRs have been evaluated in clinical studies to generate evidence for clinical decision-making in oncology.Methods and analysisWe will do a systematic literature search in MEDLINE (PubMed), Web of Science, Scopus and WHO international clinical trials registry platform to identify clinical studies (including protocols of ongoing studies), with either experimental or observational design, that aim to answer a clinical question and explore treatment sequencing issues in oncology using the concept of DTR. Data extraction will comprise information concerning cancer disease, clinical setting, treatments, tailoring variables, decision rules, decision points and outcomes, type of data, study design and statistical methods used for DTR evaluation. The review will be conducted according to Joanna Briggs Institute Reviewer’s manual for scoping reviews. No patients will be involved.Ethics and disseminationEthics committee approval is not required as this scoping review will undertake secondary analysis of published literature. Results will be disseminated through a peer-reviewed scientific journal and presented in relevant conferences. This scoping review will provide a better understanding of the methods used to generate evidence on treatment sequencing in oncology and will contribute to the identification of knowledge and methodological gaps that should be addressed.

BACKGROUND Contact tracing is a fundamental intervention in Public Health. When systematically applied, contact tracing enables the breaking of chains of transmission, an issue of special importance in the control of COVID-19 transmission. The capacity to perform contact tracing is influenced by availability of resources, prompting the need to estimate its effectiveness threshold relative to pandemic variations. This effectiveness threshold may be indirectly estimated by calculating the proportion of COVID-19 cases arising from high-risk contacts. OBJECTIVE To study the proportion of COVID-19 cases in high-risk contacts quarantined through contact tracing and its potential use as a pandemic control indicator. METHODS The research team used the data on COVID-19 collected by the Portuguese Directorate-General of Health and compiled by the Data Science for Social Good initiative. The team built an epidemiological compartmental model to simulate infection flow. We established parameters to assess infection dynamics, the influence of different variants, and vaccine efficacy. Two simulations were built: the first (A) adjusting for the presence and absence of variants or vaccination and a second (B) maximizing infection risk in individuals identified as high-risk contacts considering only one variant. The daily proportion of infected cases arising from high-risk contacts was calculated in both simulations, as was the effectiveness threshold of contact tracing. RESULTS An inverse relationship was found between the values of estimated proportion for high-risk contacts and the number of new cases in both simulations (correlations of -0.71 and -0.76, respectively). A parallel analysis of simulations’ results accounting for different variants and a potential protective effect from vaccination exhibits significant overlap. Simulation A had an effectiveness threshold for contact tracing of 1.93 (PPV = 71.7%) and simulation B had a value of 0.07 (PPV = 72.5%). CONCLUSIONS Our results highlight that a diminishing proportion of cases in exposed individuals vis-à-vis new cases is an indirect indicator of diminishing efficacy of contact tracing. The models employed also allowed us to define a value for the effectiveness threshold of contact tracing considering its role as a key pandemic mitigation tool. The lessons derived from the application of our proposed methodology and the results we obtained are an important starting point to use data from identified high-risk contacts for COVID-19 to define the infection dynamics of the SARS-CoV-2 virus. We identified scenarios and limitations that this synthetic indicator might bring to support decision-making by health authorities and policymakers.

Introduction: Phase IV trials evaluate drugs' efficacy, safety, and tolerability in a realworld setting, which may provide evidence related to the safety of approved drugs. This study aimed to characterize the phase IV clinical trials registered at ClinicalTrials.gov targeting COVID-19 and reflect on future needs for post-marketing clinical trials. Methods: A descriptive cross-sectional study was performed in the ClinitalTrials.gov database with phase IV clinical trials addressed to COVID-19. The search was carried out on March 23rd, 2021, considering search filters for this disease. Results: A total of 146 protocols were retrieved through a structured search. The results showed the need to promote new, blinded, and larger sample-size phase IV clinical trials. 93.9% of the clinical trials were funded by individuals, universities, and organizations (category "other" funders), and 56.8% were open-label. America and Europe played a more critical role in phase IV clinical trials, with the former leading with 58 trials spread across five countries and the latter with 38 trials in 17 countries. More than two-thirds of the trials (69.8%) included 500 participants. Conclusions: For the observed period, phase IV clinical trials registered in the ClinicalTrials.gov were dominated by short-term follow-up, open-label designs, small sample sizes, funded mainly by individuals, universities, and organizations, and centered mainly in America and Europe. The methodological features of future studies should be emphasized, namely adequate sample sizes, for which appropriate funding for the implementation of these studies is paramount.

Background Contact tracing is a fundamental intervention in public health. When systematically applied, it enables the breaking of chains of transmission, which is important for controlling COVID-19 transmission. In theoretically perfect contact tracing, all new cases should occur among quarantined individuals, and an epidemic should vanish. However, the availability of resources influences the capacity to perform contact tracing. Therefore, it is necessary to estimate its effectiveness threshold. We propose that this effectiveness threshold may be indirectly estimated using the ratio of COVID-19 cases arising from quarantined high-risk contacts, where higher ratios indicate better control and, under a threshold, contact tracing may fail and other restrictions become necessary. Objective This study assessed the ratio of COVID-19 cases in high-risk contacts quarantined through contact tracing and its potential use as an ancillary pandemic control indicator. Methods We built a 6-compartment epidemiological model to emulate COVID-19 infection flow according to publicly available data from Portuguese authorities. Our model extended the usual susceptible-exposed-infected-recovered model by adding a compartment Q with individuals in mandated quarantine who could develop infection or return to the susceptible pool and a compartment P with individuals protected from infection because of vaccination. To model infection dynamics, data on SARS-CoV-2 infection risk (IR), time until infection, and vaccine efficacy were collected. Estimation was needed for vaccine data to reflect the timing of inoculation and booster efficacy. In total, 2 simulations were built: one adjusting for the presence and absence of variants or vaccination and another maximizing IR in quarantined individuals. Both simulations were based on a set of 100 unique parameterizations. The daily ratio of infected cases arising from high-risk contacts (q estimate) was calculated. A theoretical effectiveness threshold of contact tracing was defined for 14-day average q estimates based on the classification of COVID-19 daily cases according to the pandemic phases and was compared with the timing of population lockdowns in Portugal. A sensitivity analysis was performed to understand the relationship between different parameter values and the threshold obtained. Results An inverse relationship was found between the q estimate and daily cases in both simulations (correlations >0.70). The theoretical effectiveness thresholds for both simulations attained an alert phase positive predictive value of >70% and could have anticipated the need for additional measures in at least 4 days for the second and fourth lockdowns. Sensitivity analysis showed that only the IR and booster dose efficacy at inoculation significantly affected the q estimates. Conclusions We demonstrated the impact of applying an effectiveness threshold for contact tracing on decision-making. Although only theoretical thresholds could be provided, their relationship with the number of confirmed cases and the prediction of pandemic phases shows the role as an indirect indicator of the efficacy of contact tracing.