Cross-sectional study to assess the impact of the COVID-19 pandemic on healthcare services and clinical admissions using statistical analysis and discovering hotspots in three regions of the Greater Toronto Area.

OBJECTIVES: The COVID-19 pandemic disrupted healthcare services, leading to the cancellation of non-urgent tests, screenings and procedures, a shift towards remote consultations, stalled childhood immunisations and clinic closures which had detrimental effects across the healthcare system. This study investigates the impact of the COVID-19 pandemic on clinical admissions and healthcare quality in the Peel, York and Toronto regions within the Greater Toronto Area (GTA). DESIGN: In a cross-sectional study, the negative impact of the pandemic on various healthcare sectors, including preventive and primary care (PPC), the emergency department (ED), alternative level of care (ALC) and imaging, procedures and surgeries is investigated. Study questions include assessing impairments caused by the COVID-19 pandemic and discovering hotspots and critical subregions that require special attention to recover. The measuring technique involves comparing the number of cases during the COVID-19 pandemic with before that, and determining the difference in percentage. Statistical analyses (Mann-Whitney U test, analysis of variance, Dunn's test) is used to evaluate sector-specific changes and inter-relationships. SETTING: This work uses primary data which were collected by the Black Creek Community Health Centre. The study population was from three regions of GTA, namely, the city of Toronto, York and Peel. For all health sectors, the sample size was large enough to have a statistical power of 0.95 to capture 1% variation in the number of cases during the COVID-19 pandemic compared with before that. RESULTS: All sectors experienced a significant decline in patient volume during the pandemic. ALC admissions surged in some areas, while IPS patients faced delays. Surgery waitlists increased by an average of 9.75%, and completed IPS procedures decreased in several subregions. CONCLUSIONS: The COVID-19 pandemic had a universally negative impact on healthcare sectors across various subregions. Identification of the hardest-hit subregions in each sector can assist health officials in crafting recovery policies.

Knowing the unknown: The underestimation of monkeypox cases. Insights and implications from an integrative review of the literature.

Monkeypox is an emerging zoonotic disease caused by the monkeypox virus, which is an infectious agent belonging to the genus Orthopoxvirus. Currently, commencing from the end of April 2022, an outbreak of monkeypox is ongoing, with more than 43,000 cases reported as of 23 August 2022, involving 99 countries and territories across all the six World Health Organization (WHO) regions. On 23 July 2022, the Director-General of the WHO declared monkeypox a global public health emergency of international concern (PHEIC), since the outbreak represents an extraordinary, unusual, and unexpected event that poses a significant risk for international spread, requiring an immediate, coordinated international response. However, the real magnitude of the burden of disease could be masked by failures in ascertainment and under-detection. As such, underestimation affects the efficiency and reliability of surveillance and notification systems and compromises the possibility of making informed and evidence-based policy decisions in terms of the adoption and implementation of ad hoc adequate preventive measures. In this review, synthesizing 53 papers, we summarize the determinants of the underestimation of sexually transmitted diseases, in general, and, in particular, monkeypox, in terms of all their various components and dimensions (under-ascertainment, underreporting, under-detection, under-diagnosis, misdiagnosis/misclassification, and under-notification).

The effect of leading edge porosity on airfoil turbulence interaction noise.

Airfoil turbulence interaction noise and the flow field up to and over the porous leading edge is experimentally studied. The porous leading edges were of the same base triply periodic minimal surface structure with varying porosity to enable us to understand how the porosity, permeability, and pore size affect the generated turbulence interaction noise. The turbulent flow was generated by means of a passive turbulence grid that does not affect the normal background noise of the wind tunnel. Far-field noise results were obtained from a polar microphone array to assess the directivity of the sound as well as the narrowband frequency contributions. Far-field noise results demonstrate that increasing porosity reduces the turbulence interaction noise over low-to-mid frequencies, with a penalty of a high frequency noise increase. Flow measurement results indicate hydrodynamic penetration of the flow into the porous structure at the leading edge. Furthermore, the two-point correlation analysis of the velocity fluctuations approaching the leading edge shows that the turbulent structures approaching the solid leading edge appear to deform into more two-dimensional structures, whereas in the case of the porous leading edge, the turbulent structures appear to retain a strong spanwise coherence up to the point of hydrodynamic penetration.