A Characteristic Chest Radiographic Pattern in the Setting of the COVID-19 Pandemic.

PURPOSE: To determine the utility of chest radiography in aiding clinical diagnosis of coronavirus disease 2019 (COVID-19) utilizing reverse-transcription polymerase chain reaction (RT-PCR) as the standard of comparison. MATERIALS AND METHODS: A retrospective study was performed of persons under investigation for COVID-19 presenting to this institution during the exponential growth phase of the COVID-19 outbreak in New Orleans (March 13-25, 2020). Three hundred seventy-six in-hospital chest radiographic examinations for 366 individual patients were reviewed along with concurrent RT-PCR tests. Two experienced radiologists categorized each chest radiograph as characteristic, nonspecific, or negative in appearance for COVID-19, utilizing well-documented COVID-19 imaging patterns. Chest radiograph categorization was compared against RT-PCR results to determine the utility of chest radiography in diagnosing COVID-19. RESULTS: Of the 366 patients, the study consisted of 178 male (49%) and 188 female (51%) patients with a mean age of 52.7 years (range, 17 to 98 years). Of the 376 chest radiographic examinations, 37 (10%) exhibited the characteristic COVID-19 appearance; 215 (57%) exhibited the nonspecific appearance; and 124 (33%) were considered negative for a pulmonary abnormality. Of the 376 RT-PCR tests evaluated, 200 (53%) were positive and 176 (47%) were negative. RT-PCR tests took an average of 2.5 days ± 0.7 to provide results. Sensitivity and specificity for correctly identifying COVID-19 with a characteristic chest radiographic pattern was 15.5% (31/200) and 96.6% (170/176), with a positive predictive value and negative predictive value of 83.8% (31/37) and 50.1% (170/339), respectively. CONCLUSION: The presence of patchy and/or confluent, bandlike ground-glass opacity or consolidation in a peripheral and mid to lower lung zone distribution on a chest radiograph obtained in the setting of pandemic COVID-19 was highly suggestive of severe acute respiratory syndrome coronavirus 2 infection and should be used in conjunction with clinical judgment to make a diagnosis.© RSNA, 2020.

Indirect effects of the COVID-19 pandemic on malaria intervention coverage, morbidity, and mortality in Africa: a geospatial modelling analysis.

BACKGROUND: Substantial progress has been made in reducing the burden of malaria in Africa since 2000, but those gains could be jeopardised if the COVID-19 pandemic affects the availability of key malaria control interventions. The aim of this study was to evaluate plausible effects on malaria incidence and mortality under different levels of disruption to malaria control. METHODS: Using an established set of spatiotemporal Bayesian geostatistical models, we generated geospatial estimates across malaria-endemic African countries of the clinical case incidence and mortality of malaria, incorporating an updated database of parasite rate surveys, insecticide-treated net (ITN) coverage, and effective treatment rates. We established a baseline estimate for the anticipated malaria burden in Africa in the absence of COVID-19-related disruptions, and repeated the analysis for nine hypothetical scenarios in which effective treatment with an antimalarial drug and distribution of ITNs (both through routine channels and mass campaigns) were reduced to varying extents. FINDINGS: We estimated 215·2 (95% uncertainty interval 143·7-311·6) million cases and 386·4 (307·8-497·8) thousand deaths across malaria-endemic African countries in 2020 in our baseline scenario of undisrupted intervention coverage. With greater reductions in access to effective antimalarial drug treatment, our model predicted increasing numbers of cases and deaths: 224·1 (148·7-326·8) million cases and 487·9 (385·3-634·6) thousand deaths with a 25% reduction in antimalarial drug coverage; 233·1 (153·7-342·5) million cases and 597·4 (468·0-784·4) thousand deaths with a 50% reduction; and 242·3 (158·7-358·8) million cases and 715·2 (556·4-947·9) thousand deaths with a 75% reduction. Halting planned 2020 ITN mass distribution campaigns and reducing routine ITN distributions by 25%-75% also increased malaria burden to a total of 230·5 (151·6-343·3) million cases and 411·7 (322·8-545·5) thousand deaths with a 25% reduction; 232·8 (152·3-345·9) million cases and 415·5 (324·3-549·4) thousand deaths with a 50% reduction; and 234·0 (152·9-348·4) million cases and 417·6 (325·5-553·1) thousand deaths with a 75% reduction. When ITN coverage and antimalarial drug coverage were synchronously reduced, malaria burden increased to 240·5 (156·5-358·2) million cases and 520·9 (404·1-691·9) thousand deaths with a 25% reduction; 251·0 (162·2-377·0) million cases and 640·2 (492·0-856·7) thousand deaths with a 50% reduction; and 261·6 (167·7-396·8) million cases and 768·6 (586·1-1038·7) thousand deaths with a 75% reduction. INTERPRETATION: Under pessimistic scenarios, COVID-19-related disruption to malaria control in Africa could almost double malaria mortality in 2020, and potentially lead to even greater increases in subsequent years. To avoid a reversal of two decades of progress against malaria, averting this public health disaster must remain an integrated priority alongside the response to COVID-19. FUNDING: Bill and Melinda Gates Foundation; Channel 7 Telethon Trust, Western Australia.

Radiologic chest CT findings from COVID-19 in Orleans Parish, Louisiana.

Orleans Parish in Louisiana is in the midst of an exponentially increasing number of patient admissions with COVID-19 and respiratory symptoms. Patients have been described having CT findings most consistent with an early-stage (<7 days from symptoms onset) or an advanced stage (8-14 days from symptoms onset). We describe and illustrate those early and advanced stage CT findings from patients with documented COVID-19 who have been admitted to University Medical Center in New Orleans, Louisiana.