Limits to Forecasting Precision for Outbreaks of Directly Transmitted Diseases

BACKGROUND: Early warning systems for outbreaks of infectious diseases are an important application of the ecological theory of epidemics. A key variable predicted by early warning systems is the final outbreak size. However, for directly transmitted diseases, the stochastic contact process by which outbreaks develop entails fundamental limits to the precision with which the final size can be predicted. METHODS AND FINDINGS: I studied how the expected final outbreak size and the coefficient of variation in the final size of outbreaks scale with control effectiveness and the rate of infectious contacts in the simple stochastic epidemic. As examples, I parameterized this model with data on observed ranges for the basic reproductive ratio (R (0)) of nine directly transmitted diseases. I also present results from a new model, the simple stochastic epidemic with delayed-onset intervention, in which an initially supercritical outbreak (R (0) > 1) is brought under control after a delay. CONCLUSION: The coefficient of variation of final outbreak size in the subcritical case (R (0) < 1) will be greater than one for any outbreak in which the removal rate is less than approximately 2.41 times the rate of infectious contacts, implying that for many transmissible diseases precise forecasts of the final outbreak size will be unattainable. In the delayed-onset model, the coefficient of variation (CV) was generally large (CV > 1) and increased with the delay between the start of the epidemic and intervention, and with the average outbreak size. These results suggest that early warning systems for infectious diseases should not focus exclusively on predicting outbreak size but should consider other characteristics of outbreaks such as the timing of disease emergence

Lumping or splitting: seeking the preferred areal unit for health geography studies

BACKGROUND: Findings are compared on geographic variation of incident and late-stage cancers across Connecticut using different areal units for analysis. RESULTS: Few differences in results were found for analyses across areal units. Global clustering of incident prostate and breast cancer cases was apparent regardless of the level of geography used. The test for local clustering found approximately the same locales, populations at risk and estimated effects. However, some discrepancies were uncovered. CONCLUSION: In the absence of conditions calling for surveillance of small area cancer clusters ('hot spots'), the rationale for accepting the burdens of preparing data at levels of geography finer than the census tract may not be compelling

Automated Detection of Infectious Disease Outbreaks in Hospitals: A Retrospective Cohort Study

Susan Huang and colleagues describe an automated statistical software, WHONET-SaTScan, its application in a hospital, and the potential it has to identify hospital infection clusters that had escaped routine detection

Simulated Anthrax Attacks and Syndromic Surveillance

Bioterrorism surveillance systems can be assessed using modeling to simulate real-world attacks

The geographic distribution of breast cancer incidence in Massachusetts 1988 to 1997, adjusted for covariates

BACKGROUND: The aims of this study were to determine whether observed geographic variations in breast cancer incidence are random or statistically significant, whether statistically significant excesses are temporary or time-persistent, and whether they can be explained by covariates such as socioeconomic status (SES) or urban/rural status? RESULTS: A purely spatial analysis found fourteen geographic areas that deviated significantly from randomness: ten with higher incidence rates than expected, four lower than expected. After covariate adjustment, three of the ten high areas remained statistically significant and one new high area emerged. The space-time analysis identified eleven geographic areas as statistically significant, seven high and four low. After covariate adjustment, four of the seven high areas remained statistically significant and a fifth high area also identified in the purely spatial analysis emerged. CONCLUSIONS: These analyses identify geographic areas with invasive breast cancer incidence higher or lower than expected, the times of their excess, and whether or not their status is affected when the model is adjusted for risk factors. These surveillance findings can be a sound starting point for the epidemiologist and has the potential of monitoring time trends for cancer control activities

Meat intake, cooking-related mutagens and risk of colorectal adenoma in a sigmoidoscopy-based case-control study

Reported habits of red meat consumption, particularly red meat that has been cooked to the degree termed ‘well-done', is a positive risk factor for colorectal cancer. Under high, pyrolytic temperatures, heterocyclic amines (HCA) and benzo[a]pyrene (BP) molecules can form inside and on the surface of red meat, respectively. These compounds are precursors that are metabolically converted to compounds known to act as mutagens and carcinogens in animal models, yet their role in human colorectal carcinogenesis remains to be clarified. We investigated whether intake of these compounds is associated with risk of colorectal adenoma in the context of a polyp-screening study conducted in Southern California. Using a database of individual HCAs and BP in meats of various types and subjected to specified methods and degrees of cooking, we estimated nanogram consumption of 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine, 2-amino-3,4,8-trimethylimidazo[4,5-f] quinoxaline, 2-amino-3,8-dimethylimidazo[4,5-f]quinoxaline and benzo[a]pyrene (BP). We observed a 6% increased risk of large (>1 cm) adenoma per 10 ng/day consumption of BP [OR = 1.06 (95% CI, 1.00-1.12), P (trend) = 0.04]. A major source of BP is red meat exposed to a naked flame, as occurs during the barbecuing process. Consistent with this finding an incremental increase of 10 g of barbecued red meat per day was associated with a 29% increased risk of large adenoma [OR = 1.29 (95% CI, 1.02-1.63), P (trend) = 0.04]. Individuals in the top quintile of barbecued red meat intake were at increased risk of large adenoma [OR = 1.90 (95% CI, 1.04-3.45)], compared with never consuming barbecued red meat. The consumption of oven-broiled red meat was inversely related to adenoma risk compared with non-consumers [OR = 0.49 (95% CI, 0.28-0.85)]. We did not identify any association with consumption of individual HCAs and colorectal adenoma risk. These results support the hypothesis that BP contributes to colorectal carcinogenesi

A Space–Time Permutation Scan Statistic for Disease Outbreak Detection

BACKGROUND: The ability to detect disease outbreaks early is important in order to minimize morbidity and mortality through timely implementation of disease prevention and control measures. Many national, state, and local health departments are launching disease surveillance systems with daily analyses of hospital emergency department visits, ambulance dispatch calls, or pharmacy sales for which population-at-risk information is unavailable or irrelevant. METHODS AND FINDINGS: We propose a prospective space–time permutation scan statistic for the early detection of disease outbreaks that uses only case numbers, with no need for population-at-risk data. It makes minimal assumptions about the time, geographical location, or size of the outbreak, and it adjusts for natural purely spatial and purely temporal variation. The new method was evaluated using daily analyses of hospital emergency department visits in New York City. Four of the five strongest signals were likely local precursors to citywide outbreaks due to rotavirus, norovirus, and influenza. The number of false signals was at most modest. CONCLUSION: If such results hold up over longer study times and in other locations, the space–time permutation scan statistic will be an important tool for local and national health departments that are setting up early disease detection surveillance systems

Early Detection of Tuberculosis Outbreaks among the San Francisco Homeless: Trade-Offs Between Spatial Resolution and Temporal Scale

BACKGROUND: San Francisco has the highest rate of tuberculosis (TB) in the U.S. with recurrent outbreaks among the homeless and marginally housed. It has been shown for syndromic data that when exact geographic coordinates of individual patients are used as the spatial base for outbreak detection, higher detection rates and accuracy are achieved compared to when data are aggregated into administrative regions such as zip codes and census tracts. We examine the effect of varying the spatial resolution in the TB data within the San Francisco homeless population on detection sensitivity, timeliness, and the amount of historical data needed to achieve better performance measures. METHODS AND FINDINGS: We apply a variation of space-time permutation scan statistic to the TB data in which a patient's location is either represented by its exact coordinates or by the centroid of its census tract. We show that the detection sensitivity and timeliness of the method generally improve when exact locations are used to identify real TB outbreaks. When outbreaks are simulated, while the detection timeliness is consistently improved when exact coordinates are used, the detection sensitivity varies depending on the size of the spatial scanning window and the number of tracts in which cases are simulated. Finally, we show that when exact locations are used, smaller amount of historical data is required for training the model. CONCLUSION: Systematic characterization of the spatio-temporal distribution of TB cases can widely benefit real time surveillance and guide public health investigations of TB outbreaks as to what level of spatial resolution results in improved detection sensitivity and timeliness. Trading higher spatial resolution for better performance is ultimately a tradeoff between maintaining patient confidentiality and improving public health when sharing data. Understanding such tradeoffs is critical to managing the complex interplay between public policy and public health. This study is a step forward in this direction

Vaccine Preventability of Meningococcal Clone, Greater Aachen Region, Germany

An emerging serogroup B clone can be prevented by vaccines