Showing papers by "Ben S. Cooper published in 2009"

The Severity of Pandemic H1N1 Influenza in the United States, from April to July 2009: A Bayesian Analysis

Abstract: Background: Accurate measures of the severity of pandemic (H1N1) 2009 influenza (pH1N1) are needed to assess the likely impact of an anticipated resurgence in the autumn in the Northern Hemisphere. Severity has been difficult to measure because jurisdictions with large numbers of deaths and other severe outcomes have had too many cases to assess the total number with confidence. Also, detection of severe cases may be more likely, resulting in overestimation of the severity of an average case. We sought to estimate the probabilities that symptomatic infection would lead to hospitalization, ICU admission, and death by combining data from multiple sources. Methods and Findings: We used complementary data from two US cities: Milwaukee attempted to identify cases of medically attended infection whether or not they required hospitalization, while New York City focused on the identification of hospitalizations, intensive care admission or mechanical ventilation (hereafter, ICU), and deaths. New York data were used to estimate numerators for ICU and death, and two sources of data—medically attended cases in Milwaukee or self-reported influenza-like illness (ILI) in New York—were used to estimate ratios of symptomatic cases to hospitalizations. Combining these data with estimates of the fraction detected for each level of severity, we estimated the proportion of symptomatic patients who died (symptomatic case-fatality ratio, sCFR), required ICU (sCIR), and required hospitalization (sCHR), overall and by age category. Evidence, prior information, and associated uncertainty were analyzed in a Bayesian evidence synthesis framework. Using medically attended cases and estimates of the proportion of symptomatic cases medically attended, we estimated an sCFR of 0.048% (95% credible interval [CI] 0.026%–0.096%), sCIR of 0.239% (0.134%–0.458%), and sCHR of 1.44% (0.83%–2.64%). Using self-reported ILI, we obtained estimates approximately 7–96 lower. sCFR and sCIR appear to be highest in persons aged 18 y and older, and lowest in children aged 5–17 y. sCHR appears to be lowest in persons aged 5–17; our data were too sparse to allow us to determine the group in which it was the highest. Conclusions: These estimates suggest that an autumn–winter pandemic wave of pH1N1 with comparable severity per case could lead to a number of deaths in the range from considerably below that associated with seasonal influenza to slightly higher, but with the greatest impact in children aged 0–4 and adults 18–64. These estimates of impact depend on assumptions about total incidence of infection and would be larger if incidence of symptomatic infection were higher or shifted toward adults, if viral virulence increased, or if suboptimal treatment resulted from stress on the health care system; numbers would decrease if the total proportion of the population symptomatically infected were lower than assumed. Please see later in the article for the Editors’ Summary.

Hedging against Antiviral Resistance during the Next Influenza Pandemic Using Small Stockpiles of an Alternative Chemotherapy

Abstract: Background The effectiveness of single-drug antiviral interventions to reduce morbidity and mortality during the next influenza pandemic will be substantially weakened if transmissible strains emerge which are resistant to the stockpiled antiviral drugs. We developed a mathematical model to test the hypothesis that a small stockpile of a secondary antiviral drug could be used to mitigate the adverse consequences of the emergence of resistant strains. Methods and Findings We used a multistrain stochastic transmission model of influenza to show that the spread of antiviral resistance can be significantly reduced by deploying a small stockpile (1% population coverage) of a secondary drug during the early phase of local epidemics. We considered two strategies for the use of the secondary stockpile: early combination chemotherapy (ECC; individuals are treated with both drugs in combination while both are available); and sequential multidrug chemotherapy (SMC; individuals are treated only with the secondary drug until it is exhausted, then treated with the primary drug). We investigated all potentially important regions of unknown parameter space and found that both ECC and SMC reduced the cumulative attack rate (AR) and the resistant attack rate (RAR) unless the probability of emergence of resistance to the primary drug pA was so low (less than 1 in 10,000) that resistance was unlikely to be a problem or so high (more than 1 in 20) that resistance emerged as soon as primary drug monotherapy began. For example, when the basic reproductive number was 1.8 and 40% of symptomatic individuals were treated with antivirals, AR and RAR were 67% and 38% under monotherapy if pA = 0.01. If the probability of resistance emergence for the secondary drug was also 0.01, then SMC reduced AR and RAR to 57% and 2%. The effectiveness of ECC was similar if combination chemotherapy reduced the probabilities of resistance emergence by at least ten times. We extended our model using travel data between 105 large cities to investigate the robustness of these resistance-limiting strategies at a global scale. We found that as long as populations that were the main source of resistant strains employed these strategies (SMC or ECC), then those same strategies were also effective for populations far from the source even when some intermediate populations failed to control resistance. In essence, through the existence of many wild-type epidemics, the interconnectedness of the global network dampened the international spread of resistant strains. Conclusions Our results indicate that the augmentation of existing stockpiles of a single anti-influenza drug with smaller stockpiles of a second drug could be an effective and inexpensive epidemiological hedge against antiviral resistance if either SMC or ECC were used. Choosing between these strategies will require additional empirical studies. Specifically, the choice will depend on the safety of combination therapy and the synergistic effect of one antiviral in suppressing the emergence of resistance to the other antiviral when both are taken in combination.

Using a Longitudinal Model to Estimate the Effect of Methicillin-resistant Staphylococcus aureus Infection on Length of Stay in an Intensive Care Unit

Abstract: Health-care-associated methicillin-resistant Staphylococcus aureus (MRSA) infection may cause increased hospital stay, or sometimes death. Quantifying this effect is complicated because the exposure is time dependent: infection may prolong hospital stay, while longer stays increase infection risk. In this paper, the authors overcome these problems by using a multinomial longitudinal model to estimate the daily probability of death and discharge. They then extend the basic model to estimate how the effect of MRSA infection varies over time and to quantify number of excess days in the intensive care unit due to infection. They found that infection decreased the relative risk of discharge (relative risk ratio = 0.68, 95% credible interval: 0.54, 0.82). Infection on the first day of admission resulted in a mean extra stay of 0.3 days (95% credible interval: 0.1, 0.5) for a patient with an Acute Physiology and Chronic Health Evaluation II score of 10 and 1.2 days (95% credible interval: 0.5, 2.0) for a patient with a score of 30. The decrease in the relative risk of discharge remained fairly constant with day of MRSA infection but was slightly stronger closer to the start of infection. Results confirm the importance of MRSA infection in increasing stay in an intensive care unit but suggest that previous work may have systematically overestimated the effect size.

The impact of public health control measures during the SARS epidemic in mainland China

Abstract: We tracked the effective reproductive number (Rt) over time to assess the impact of important public health control measures in the five most SARS-affected geographic areas in mainland China. As soon as the Chinese authorities gained full control of all activities to combat SARS, Rt decreased dramatically and consistently below one. Many control measures that seriously affected public life were implemented afterwards, i.e., when the epidemic was already dying down.

Transmission of SARS in three Chinese hospitals.

Abstract: Summary Objective To quantify the transmissibility of severe acute respiratory syndrome (SARS) in hospitals in mainland China and to assess the effectiveness of control measures. Methods We report key epidemiological details of three major hospital outbreaks of SARS in mainland China, and estimate the evolution of the effective reproduction number in each of the three hospitals during the course of the outbreaks. Results The three successive hospital outbreaks infected 41, 99 and 91 people of whom 37%, 60% and 70% were hospital staff. These cases resulted in 33 deaths, five of which occurred in hospital staff. In a multivariate logistic regression, age and whether or not the case was a healthcare worker (HCW) were found to be significant predictors of mortality. The estimated effective reproduction numbers (95% CI) for the three epidemics peaked at 8 (5, 11), 9 (4, 14) and 12 (7, 17). In all three hospitals the epidemics were rapidly controlled, bringing the reproduction number below one within 25, 10 and 5 days respectively. Conclusions This work shows that in three major hospital epidemics in Beijing and Tianjin substantially higher rates of transmission were initially observed than those seen in the community. In all three cases the hospital epidemics were rapidly brought under control, with the time to successful control becoming shorter in each successive outbreak.