All-cause mortality during COVID-19 pandemic in Peru

From risk factors to disease situations: A socio-spatial analysis of COVID-19 experiences in Lima, Peru

The goal of this qualitative research study, part of an interdisciplinary project, was to understand the overlapping geographical distribution of COVID-19 and tuberculosis burden in Lima. Using an ethnographic approach, we applied the concept of disease situations to explore how inhabitants' social and spatial situatedness affected their capacity to respond to the pandemic. Our results show that for some populations in Lima, the risk to develop COVID-19 did not emerge suddenly; it could be traced back to situations of living under subsistence models, relying on unstable sources of income, facing food insecurity, depending on certain mechanisms of social protection, residing in precarious living environments and lacking access to quality health care. These populations did not only have less resources to adjust to changes in daily life induced by the pandemic; they were also forced to constantly weigh the risk of COVID-19 against other pressing needs and potentially face increased risks when control measures were actually followed. Pre-existing social networks played fundamental roles as sources of emotional and material support. The lens of disease situations can help to identify and explain spatial and social configurations that enhance vulnerability, as well as resilience mechanisms that are in place to deal with crises. This perspective could inform the design of contextualised prevention and response strategies around health risks in cities as diverse as Lima, whilst building on existing resources at local levels.

Geospatial analysis of cardiovascular mortality before and during the COVID-19 pandemic in Peru: analysis of the national death registry to support emergency management in Peru

Background

COVID-19 has led to significant global mortality, with Peru being among the countries most affected. While pre-existing comorbidities have been linked to most cases, the exact distribution of fatalities within the country remains unclear. We aimed to assess deaths attributed to cardiovascular diseases (CVD) before and during the COVID-19 pandemic across various regions and provinces in Peru.

Methods

An observational georeferencing study was designed. Peru faced four waves of COVID-19 over three years, with variable impacts across its three regions (Coast, Highlands, and Jungle). Deaths related to cardiovascular diseases, such as heart failure (HF), arrhythmia, acute myocardial infarction (AMI), strokes, and acute coronary syndrome, were examined as primary variables. The study period spanned pre-pandemic years (2017-2019) and pandemic years (2020-2021), utilizing death data from the National Death Information System (SINADEF). The georeferencing analysis was conducted using ArcGIS v10.3.

Results

A total of 28,197 deaths were recorded during the study period, with significant increases during the pandemic (2020-2021). Cardiovascular deaths were disproportionately higher during the pandemic, totaling 19,376 compared to 8,821 in the pre-pandemic period (p < 0.001). AMI and HF were the leading causes of mortality, showing significant increases from the pre-pandemic (5,573 and 2,584 deaths) to the pandemic period (12,579 and 5,628 deaths), respectively. Deaths due to CVD predominantly affected individuals aged over 60, with significant increases between the two study periods (7,245 vs. 16,497 deaths, p = 0.002). Geospatial analysis revealed regional disparities in CVD mortality, highlighting provinces like Lima and Callao as COVID-19 critical areas. The substantial increase in cardiovascular deaths during the COVID-19 pandemic in Peru showed distinctive patterns across regions and provinces.

Conclusions

Geospatial analysis identified higher-risk areas and can guide specific interventions to mitigate the impact of future health crises. Understanding the dynamic relationship between pandemics and cardiovascular health is crucial for effective public health strategies.

Integrated Management Systems (IMS) to Support and Sustain Quality One Health Services: International Lessons from the COVID-19 Pandemic by the IMIA Primary Care Working Group

OBJECTIVES

One Health considers human, animal and environment health as a continuum. The COVID-19 pandemic started with the leap of a virus from animals to humans. Integrated management systems (IMS) should provide a coherent management framework, to meet reporting requirements and support care delivery. We report IMS deployment during, and retention post the COVID-19 pandemic, and exemplar One Health use cases.

METHODS

Six volunteer members of the International Medical Association's (IMIA) Primary Care Working Group provided data about any IMS and One Health use to support the COVID-19 pandemic initiatives. We explored how IMS were: (1) Integrated with organisational strategy; (2) Utilised standardised processes, and (3) Met reporting requirements, including public health. Selected contributors provided Unified Modelling Language (UML) use case diagram for a One Health exemplar.

RESULTS

There was weak evidence of synergy between IMS and health system strategy to the COVID-19 pandemic. However, there were rapid pragmatic responses to COVID-19, not citing IMS. All health systems implemented IMS to link COVID test results, vaccine uptake and outcomes, particularly mortality and to provide patients access to test results and vaccination certification. Neither proportion of gross domestic product alone, nor vaccine uptake determined outcome. One Health exemplars demonstrated that animal, human and environmental specialists could collaborate.

CONCLUSIONS

IMS use improved the pandemic response. However, IMS use was pragmatic rather than utilising an international standard, with some of their benefits lost post-pandemic. Health systems should incorporate IMS that enables One Health approaches as part of their post COVID-19 pandemic preparedness.