Longitudinal Assessment of Diagnostic Test Performance Over the Course of Acute SARS-CoV-2 Infection.

BACKGROUND: Serial screening is critical for restricting spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by facilitating timely identification of infected individuals to interrupt transmission. Variation in sensitivity of different diagnostic tests at different stages of infection has not been well documented. METHODS: In a longitudinal study of 43 adults newly infected with SARS-CoV-2, all provided daily saliva and nasal swabs for quantitative reverse transcription polymerase chain reaction (RT-qPCR), Quidel SARS Sofia antigen fluorescent immunoassay (FIA), and live virus culture. RESULTS: Both RT-qPCR and Quidel SARS Sofia antigen FIA peaked in sensitivity during the period in which live virus was detected in nasal swabs, but sensitivity of RT-qPCR tests rose more rapidly prior to this period. We also found that serial testing multiple times per week increases the sensitivity of antigen tests. CONCLUSIONS: RT-qPCR tests are more effective than antigen tests at identifying infected individuals prior to or early during the infectious period and thus for minimizing forward transmission (given timely results reporting). All tests showed >98% sensitivity for identifying infected individuals if used at least every 3 days. Daily screening using antigen tests can achieve approximately 90% sensitivity for identifying infected individuals while they are viral culture positive.

Longitudinal assessment of diagnostic test performance over the course of acute SARS-CoV-2 infection.

WHAT IS ALREADY KNOWN ABOUT THIS TOPIC?: Diagnostic tests and sample types for SARS-CoV-2 vary in sensitivity across the infection period. WHAT IS ADDED BY THIS REPORT?: We show that both RTqPCR (from nasal swab and saliva) and the Quidel SARS Sofia FIA rapid antigen tests peak in sensitivity during the period in which live virus can be detected in nasal swabs, but that the sensitivity of RTqPCR tests rises more rapidly in the pre-infectious period. We also use empirical data to estimate the sensitivities of RTqPCR and antigen tests as a function of testing frequency. WHAT ARE THE IMPLICATIONS FOR PUBLIC HEALTH PRACTICE?: RTqPCR tests will be more effective than rapid antigen tests at identifying infected individuals prior to or early during the infectious period and thus for minimizing forward transmission (provided results reporting is timely). All modalities, including rapid antigen tests, showed >94% sensitivity to detect infection if used at least twice per week. Regular surveillance/screening using rapid antigen tests 2-3 times per week can be an effective strategy to achieve high sensitivity (>95%) for identifying infected individuals.

Socioeconomic status determines COVID-19 incidence and related mortality in Santiago, Chile.

The COVID-19 pandemic has affected cities particularly hard. Here, we provide an in-depth characterization of disease incidence and mortality and their dependence on demographic and socioeconomic strata in Santiago, a highly segregated city and the capital of Chile. Our analyses show a strong association between socioeconomic status and both COVID-19 outcomes and public health capacity. People living in municipalities with low socioeconomic status did not reduce their mobility during lockdowns as much as those in more affluent municipalities. Testing volumes may have been insufficient early in the pandemic in those places, and both test positivity rates and testing delays were much higher. We find a strong association between socioeconomic status and mortality, measured by either COVID-19-attributed deaths or excess deaths. Finally, we show that infection fatality rates in young people are higher in low-income municipalities. Together, these results highlight the critical consequences of socioeconomic inequalities on health outcomes.

Socioeconomic status determines COVID-19 incidence and related mortality in Santiago, Chile.

The current coronavirus disease 2019 (COVID-19) pandemic has impacted dense urban populations particularly hard. Here, we provide an in-depth characterization of disease incidence and mortality patterns, and their dependence on demographic and socioeconomic strata in Santiago, a highly segregated city and the capital of Chile. We find that among all age groups, there is a strong association between socioeconomic status and both mortality -measured either by direct COVID-19 attributed deaths or excess deaths- and public health capacity. Specifically, we show that behavioral factors like human mobility, as well as health system factors such as testing volumes, testing delays, and test positivity rates are associated with disease outcomes. These robust patterns suggest multiple possibly interacting pathways that can explain the observed disease burden and mortality differentials: (i) in lower socioeconomic status municipalities, human mobility was not reduced as much as in more affluent municipalities; (ii) testing volumes in these locations were insufficient early in the pandemic and public health interventions were applied too late to be effective; (iii) test positivity and testing delays were much higher in less affluent municipalities, indicating an impaired capacity of the health-care system to contain the spread of the epidemic; and (iv) infection fatality rates appear much higher in the lower end of the socioeconomic spectrum. Together, these findings highlight the exacerbated consequences of health-care inequalities in a large city of the developing world, and provide practical methodological approaches useful for characterizing COVID-19 burden and mortality in other segregated urban centers.

Climate forcing and infectious disease transmission in urban landscapes: integrating demographic and socioeconomic heterogeneity.

Urbanization and climate change are the two major environmental challenges of the 21st century. The dramatic expansion of cities around the world creates new conditions for the spread, surveillance, and control of infectious diseases. In particular, urban growth generates pronounced spatial heterogeneity within cities, which can modulate the effect of climate factors at local spatial scales in large urban environments. Importantly, the interaction between environmental forcing and socioeconomic heterogeneity at local scales remains an open area in infectious disease dynamics, especially for urban landscapes of the developing world. A quantitative and conceptual framework on urban health with a focus on infectious diseases would benefit from integrating aspects of climate forcing, population density, and level of wealth. In this paper, we review what is known about these drivers acting independently and jointly on urban infectious diseases; we then outline elements that are missing and would contribute to building such a framework.