Insurance for economic losses caused by pandemics.

Private insurance coverage for economic losses caused by pandemics is limited. While many factors contribute to reduced demand and supply, we attribute the low amount of coverage to the high levels of capital that would be required to credibly insure pandemic economic losses with cross-sectional pooling mechanisms. Pooling over time significantly reduces the required capital and therefore the cost of insurance, but as a practical matter likely requires a government with the ability to borrow and tax. We also argue that insurance for economic losses due to pandemics likely generates positive externalities for the macroeconomy. We therefore analyze the general tradeoffs associated with different ways that a government can promote such insurance.

Mathematics for demosaicking.

Digital color cameras sample the continuous color spectrum using three or more filters; however, each pixel represents a sample of only one of the color bands. This arrangement is called a mosaic. To produce a full-resolution color image, the recorded image must be processed to estimate the values of the pixels for all the other color bands. This restoration process is often called demosaicking. This paper uses stacked notation to represent the mosaicked image capture and derives the minimum mean square error (MMSE) estimator for the demosaicked image. By making common assumptions, the restoration can be computed in a cost-effective manner. Extensions to the linear method are proposed to allow adaptive behavior.

Rapid and sensitive detection of respiratory virus infections for directed antiviral treatment using R-Mix cultures.

BACKGROUND: The development of new anti-influenza drugs has led to concerns regarding the impact on healthcare costs if they are used indiscriminately. Restricting their use to proven influenza virus infections has the potential to overcome costly inappropriate therapy. However, conventional culture (CC) does not generate results quickly enough to facilitate the timely initiation of treatment, and rapid detection tests have suboptimal sensitivity. We therefore investigated a new rapid culture system (R-Mix) that contains a mixture of two cell lines and detects respiratory viruses within 24 h. OBJECTIVES: To compare the analytical sensitivity of R-Mix with CC and rapid detection methods, for the detection of influenza and other respiratory viruses. To compare the clinical sensitivity of R-Mix with CC and direct antigen detection for the detection of respiratory viruses in primary and acute care settings. STUDY DESIGN: Stock cultures of influenza virus were titrated and tested by R-Mix, ZstatFlu and FLU OIA. Stock cultures of adenovirus and parainfluenza virus type 3 were titrated and tested by R-Mix and CC. Specimens, which had previously tested positive for influenza viruses, were titrated and tested by R-Mix and CC. In symptomatic patients, the majority of whom were from primary care settings, 124 sequential specimens were tested for influenza viruses by immunofluorescent direct antigen detection and R-Mix. A separate set of 111 sequential specimens, from various symptomatic patient groups, were tested for influenza viruses by CC and R-Mix. Additionally, in acute care patients being surveillance tested during periods of immunosuppression, 155 specimens were tested for respiratory viruses (influenza A and B, parainfluenza 1-3, adenovirus and respiratory syncytial virus (RSV)) by CC and R-Mix. RESULTS: With titrated stock cultures, R-Mix showed an analytical limit of detection of ten infectious virus particles per vial for influenza A, compared with 100,000 particles per test for FLU OIA and 1,000,000 for ZstatFlu. R-Mix also showed a 100-fold greater sensitivity for the detection of influenza A and equivalent sensitivity for the detection of influenza B when compared with CC in titrated known positive specimens. Further, it showed equivalent sensitivity to CC for the detection of adenovirus and parainfluenza virus type 3 in titrated stock cultures. Among prospective specimens from symptomatic patients, the sensitivity of R-Mix, CC and direct antigen detection tests (DAT) for influenza virus detection, was 100, 67 and 66%, respectively, and the specificity was 100, 100 and 98%, respectively. In surveillance specimens from immunosuppressed patients, the sensitivities of R-Mix and CC for respiratory virus detection were equivalent. Moreover, R-Mix results were available within 24 h, and by altering the antibody staining reagents either influenza viruses, or all seven major respiratory viruses, could be detected and distinguished in a single test. CONCLUSIONS: R-Mix is a simple, rapid and sensitive system for the detection of influenza viruses that facilitates the restriction of antiviral drugs to patients with culture-confirmed infections.