Martin Kulldorff
Biographic Data
| ID | 5533944 |
|---|---|
| NAME | Martin Kulldorff |
| GIVEN NAMES | Martin |
| FAMILY NAME | Kulldorff |
| SIGNATURE | KULLDORFF M |
| AFFILIATIONS | Harvard University |
| ORCID | 0000-0002-5284-2993 |
| VERIFIED | Yes |
| TOTAL WORKS | 11 |
| TOTAL CITATIONS | 13 |
| AUTHOR COUNT | 11 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 1995 |
| LATEST PUBLICATION YEAR | 2022 |
| H-INDEX | 1 |
As Omicron Takes Hold and Other New Variants Arise, Covid-19 Testing Remains the Universally Agreed Tool to Effect Transition From Pandemic to Endemic State
The COVID-19 pandemic has caused more than 448 million cases and 6 million deaths worldwide to date. Omicron is now the dominant SARS-CoV-2 variant, making up more than 90% of cases in countries reporting sequencing data. As the pandemic continues into its third year, continued testing is a strategic and necessary tool for transitioning to an endemic state of COVID-19. Here, we address three critical topics pertaining to the transition from pande…
Counter-Point
Sequential analysis can be used as an early warning system about potential unintended consequences of health policy decisions, generating follow-up investigations, but it should not be used as causal evidence
Near Real-time Surveillance for Consequences of Health Policies Using Sequential Analysis
BACKGROUND: New health policies may have intended and unintended consequences. Active surveillance of population-level data may provide initial signals of policy effects for further rigorous evaluation soon after policy implementation. OBJECTIVE: This study evaluated the utility of sequential analysis for prospectively assessing signals of health policy impacts. As a policy example, we studied the consequences of the widely publicized Food and Dr…
Confounding Adjustment in Comparative Effectiveness Research Conducted Within Distributed Research Networks
BACKGROUND: A distributed research network (DRN) of electronic health care databases, in which data reside behind the firewall of each data partner, can support a wide range of comparative effectiveness research (CER) activities. An essential component of a fully functional DRN is the capability to perform robust statistical analyses to produce valid, actionable evidence without compromising patient privacy, data security, or proprietary interest…
Active Influenza Vaccine Safety Surveillance
BACKGROUND: Rapid safety assessment of novel vaccines, especially those targeted against pandemic influenza, is a public health priority. OBJECTIVES: Assess the feasibility of using healthcare claims data to rapidly detect influenza vaccine adverse events using sequential analytic methods. RESEARCH DESIGN: Retrospective pilot study simulating prospective surveillance using 6 cumulative monthly administrative claims data extracts. The first includ…
Real-Time Vaccine Safety Surveillance for the Early Detection of Adverse Events
BACKGROUND: Rare but serious adverse events associated with vaccines or drugs are often nearly impossible to detect in prelicensure studies and require monitoring after introduction of the agent in large populations. Sequential testing procedures are needed to detect vaccine or drug safety problems as soon as possible after introduction. OBJECTIVE: To develop and evaluate a new real-time surveillance system that uses dynamic data files and sequen…
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 ir…
An elliptic spatial scan statistic and its application to breast cancer mortality data in Northeastern United States
Evaluating cluster alarms
OBJECTIVES: This article presents a space-time scan statistic, useful for evaluating space-time cluster alarms, and illustrates the method on a recent brain cancer cluster alarms in Los Alamos, NM. METHODS: The space-time scan statistic accounts for the preselection bias and multiple testing inherent in a cluster alarm. Confounders and time trends can be adjusted for. RESULTS: The observed excess of brain cancer in Los Alamos was not statisticall…
A spatial scan statistic
The scan statistic is commonly used to test if a one dimensional point process is purely random, or if any clusters can be detected. Here it is simultaneously extended in three directions:(i) a spatial scan statistic for the detection of clusters in a multi-dimensional point process is proposed, (ii) the area of the scanning window is allowed to vary, and (iii) the baseline process may be any inhomogeneous Poisson process or Bernoulli process wit…
Spatial disease clusters
We present a new method of detection and inference for spatial clusters of a disease. To avoid ad hoc procedures to test for clustering, we have a clearly defined alternative hypothesis and our test statistic is based on the likelihood ratio. The proposed test can detect clusters of any size, located anywhere in the study region. It is not restricted to clusters that conform to predefined administrative or political borders. The test can be used …
Evaluating cluster alarms
OBJECTIVES: This article presents a space-time scan statistic, useful for evaluating space-time cluster alarms, and illustrates the method on a recent brain cancer cluster alarms in Los Alamos, NM. METHODS: The space-time scan statistic accounts for the preselection bias and multiple testing inherent in a cluster alarm. Confounders and time trends can be adjusted for. RESULTS: The observed excess of brain cancer in Los Alamos was not statisticall…
Spatial disease clusters
We present a new method of detection and inference for spatial clusters of a disease. To avoid ad hoc procedures to test for clustering, we have a clearly defined alternative hypothesis and our test statistic is based on the likelihood ratio. The proposed test can detect clusters of any size, located anywhere in the study region. It is not restricted to clusters that conform to predefined administrative or political borders. The test can be used …
A spatial scan statistic
The scan statistic is commonly used to test if a one dimensional point process is purely random, or if any clusters can be detected. Here it is simultaneously extended in three directions:(i) a spatial scan statistic for the detection of clusters in a multi-dimensional point process is proposed, (ii) the area of the scanning window is allowed to vary, and (iii) the baseline process may be any inhomogeneous Poisson process or Bernoulli process wit…
Evaluating cluster alarms
OBJECTIVES: This article presents a space-time scan statistic, useful for evaluating space-time cluster alarms, and illustrates the method on a recent brain cancer cluster alarms in Los Alamos, NM. METHODS: The space-time scan statistic accounts for the preselection bias and multiple testing inherent in a cluster alarm. Confounders and time trends can be adjusted for. RESULTS: The observed excess of brain cancer in Los Alamos was not statisticall…
An elliptic spatial scan statistic and its application to breast cancer mortality data in Northeastern United States
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 ir…
Real-Time Vaccine Safety Surveillance for the Early Detection of Adverse Events
BACKGROUND: Rare but serious adverse events associated with vaccines or drugs are often nearly impossible to detect in prelicensure studies and require monitoring after introduction of the agent in large populations. Sequential testing procedures are needed to detect vaccine or drug safety problems as soon as possible after introduction. OBJECTIVE: To develop and evaluate a new real-time surveillance system that uses dynamic data files and sequen…
Active Influenza Vaccine Safety Surveillance
BACKGROUND: Rapid safety assessment of novel vaccines, especially those targeted against pandemic influenza, is a public health priority. OBJECTIVES: Assess the feasibility of using healthcare claims data to rapidly detect influenza vaccine adverse events using sequential analytic methods. RESEARCH DESIGN: Retrospective pilot study simulating prospective surveillance using 6 cumulative monthly administrative claims data extracts. The first includ…
Confounding Adjustment in Comparative Effectiveness Research Conducted Within Distributed Research Networks
BACKGROUND: A distributed research network (DRN) of electronic health care databases, in which data reside behind the firewall of each data partner, can support a wide range of comparative effectiveness research (CER) activities. An essential component of a fully functional DRN is the capability to perform robust statistical analyses to produce valid, actionable evidence without compromising patient privacy, data security, or proprietary interest…
Counter-Point
Sequential analysis can be used as an early warning system about potential unintended consequences of health policy decisions, generating follow-up investigations, but it should not be used as causal evidence
Near Real-time Surveillance for Consequences of Health Policies Using Sequential Analysis
BACKGROUND: New health policies may have intended and unintended consequences. Active surveillance of population-level data may provide initial signals of policy effects for further rigorous evaluation soon after policy implementation. OBJECTIVE: This study evaluated the utility of sequential analysis for prospectively assessing signals of health policy impacts. As a policy example, we studied the consequences of the widely publicized Food and Dr…
As Omicron Takes Hold and Other New Variants Arise, Covid-19 Testing Remains the Universally Agreed Tool to Effect Transition From Pandemic to Endemic State
The COVID-19 pandemic has caused more than 448 million cases and 6 million deaths worldwide to date. Omicron is now the dominant SARS-CoV-2 variant, making up more than 90% of cases in countries reporting sequencing data. As the pandemic continues into its third year, continued testing is a strategic and necessary tool for transitioning to an endemic state of COVID-19. Here, we address three critical topics pertaining to the transition from pande…
Computer Science (8 works) · Medicine (8 works) · Data-Driven Disease Surveillance (6 works) · Mathematics (6 works) · Statistics (6 works) · Scan statistic (5 works) · Statistic (5 works) · Advanced Causal Inference Techniques (3 works) · Internal Medicine (3 works) · Internal Medicine (3 works)