Sumiko Mekaru | Boston Childrens Hospital (original) (raw)
Papers by Sumiko Mekaru
PLoS currents, 2015
The West Africa Ebola virus epidemic now appears to be coming to an end. In the proposed model, w... more The West Africa Ebola virus epidemic now appears to be coming to an end. In the proposed model, we simulate changes in population behavior that help to explain the observed transmission dynamics. We introduce an EVD transmission model accompanied by a model of social mobilization. The model was fit to Lofa County, Liberia through October 2014, using weekly counts of new cases reported by the US CDC. In simulation studies, we analyze the dynamics of the disease transmission with and without population behavior change, given the availability of beds in Ebola treatment units (ETUs) estimated from observed data. Only the model scenario that included individuals' behavioral change achieved a good fit to the observed case counts. Although the capacity of the Lofa County ETUs greatly increased in mid-August, our simulations show that the expansion was insufficient to alone control the outbreak. Modeling the entire outbreak without considering behavior change fit the data poorly, and ex...
Scientific reports, 2015
Challenges with alternative data sources for disease surveillance include differentiating the sig... more Challenges with alternative data sources for disease surveillance include differentiating the signal from the noise, and obtaining information from data constrained settings. For the latter, events such as increases in hospital traffic could serve as early indicators of social disruption resulting from disease. In this study, we evaluate the feasibility of using hospital parking lot traffic data extracted from high-resolution satellite imagery to augment public health disease surveillance in Chile, Argentina and Mexico. We used archived satellite imagery collected from January 2010 to May 2013 and data on the incidence of respiratory virus illnesses from the Pan American Health Organization as a reference. We developed dynamical Elastic Net multivariable linear regression models to estimate the incidence of respiratory virus illnesses using hospital traffic and assessed how to minimize the effects of noise on the models. We noted that predictions based on models fitted using a sampl...
Online Journal of Public Health Informatics, 2013
ABSTRACT Objective To introduce MoH+, HealthMap’s (HM) real-time feed of official government sour... more ABSTRACT Objective To introduce MoH+, HealthMap’s (HM) real-time feed of official government sources, and demonstrate its utility in comparing the timeliness of outbreak reporting between official and unofficial sources. Introduction Previous studies have documented significant lags in official reporting of outbreaks compared to unofficial reporting (1,2). MoH+ provides an additional tool to analyze this issue, with the unique advantage of actively gathering a wide range of streamlined official communication, including formal publications, online press releases, and social media updates. Methods Outbreaks reported by official sources were identified through MoH+ (healthmap.org/mohplus), which collects surveillance data published globally by ministries of health (MoH), other related ministries, government portals, government-affiliated organizations, and international governing bodies (Fig. 1). Reporting of these outbreaks was also identified in unofficial sources using various HM feeds including Google News, ProMED, and participatory surveillance feeds. Of the 109 outbreaks identified since May 2012, 65 were excluded as they started before data collection, 7 were excluded as they were not reported by unofficial sources, and 1 was excluded as it was a non-natural outbreak. For the remaining 36 outbreaks, the median difference in first date of report between official and unofficial sources was analyzed using a Wilcoxon sign rank test. Results Outbreak reporting in official sources lagged by a statistically significant median of 2 days (p=0.003). Among unofficial sources, online news most often (75%) was the fastest to report an outbreak, followed by ProMED (22%) and participatory surveillance (3%). Among official sources, national government affiliated institutes were most often (41%) the fastest, and repeatedly providing prompt outbreak reports were the US Centers for Disease Control and Prevention (CDC), Public Health Agency of Canada, Finnish Food Safety Authority, Health Protection Scotland, UK Health Protection Agency, and French Institute of Public Health Surveillance (FIPHS). Following such institutes were the European CDC (ECDC) with 22% of first reports of outbreaks; MoH’s (17%); and WHO (10%). There were 4 instances in which official sources reported before unofficial sources—3 by the ECDC and 1 by FIPHS. Conclusions Compared to the Chan study reporting a 16 day lag between first public communication and WHO Outbreak News (1) and the Mondor study reporting a 10 day lag between non-government and government sources (2), the present study shows a much condensed lag of 2 days between unofficial and official sources. Because the two earlier studies cover a much broader historical time frame, one explanation for the reduced lag time is increased adoption of online communication by official government agencies. However, despite such improvements in communication, the lag persists, pointing to the importance of using informal sources for outbreak surveillance. The present study was limited by small sample size, as the study is in its early stages. We will continue to gather data and all numbers will be updated in time for the presentation to reflect the larger database. Future directions of this study include characterization of official and unofficial reporting by region, language, disease, and source.
Clinical Infectious Diseases, 2014
Search query information from a clinician&amp... more Search query information from a clinician's database, UpToDate, is shown to predict influenza epidemics in the United States in a timely manner. Our results show that digital disease surveillance tools based on experts' databases may be able to provide an alternative, reliable, and stable signal for accurate predictions of influenza outbreaks.
Online Journal of Public Health Informatics, 2013
PloS one, 2012
A dearth of information obscures the true scale of the global illegal trade in wildlife. Herein, ... more A dearth of information obscures the true scale of the global illegal trade in wildlife. Herein, we introduce an automated web crawling surveillance system developed to monitor reports on illegally traded wildlife. A resource for enforcement officials as well as the general public, the freely available website, http://www.healthmap.org/wildlifetrade, provides a customizable visualization of worldwide reports on interceptions of illegally traded wildlife and wildlife products. From August 1, 2010 to July 31, 2011, publicly available English language illegal wildlife trade reports from official and unofficial sources were collected and categorized by location and species involved. During this interval, 858 illegal wildlife trade reports were collected from 89 countries. Countries with the highest number of reports included India (n = 146, 15.6%), the United States (n = 143, 15.3%), South Africa (n = 75, 8.0%), China (n = 41, 4.4%), and Vietnam (n = 37, 4.0%). Species reported as trade...
eLife, 2014
Ebola virus disease (EVD) is a complex zoonosis that is highly virulent in humans. The largest re... more Ebola virus disease (EVD) is a complex zoonosis that is highly virulent in humans. The largest recorded outbreak of EVD is ongoing in West Africa, outside of its previously reported and predicted niche. We assembled location data on all recorded zoonotic transmission to humans and Ebola virus infection in bats and primates (1976-2014). Using species distribution models, these occurrence data were paired with environmental covariates to predict a zoonotic transmission niche covering 22 countries across Central and West Africa. Vegetation, elevation, temperature, evapotranspiration, and suspected reservoir bat distributions define this relationship. At-risk areas are inhabited by 22 million people; however, the rarity of human outbreaks emphasises the very low probability of transmission to humans. Increasing population sizes and international connectivity by air since the first detection of EVD in 1976 suggest that the dynamics of human-to-human secondary transmission in contemporary...
PLoS Neglected Tropical Diseases, 2014
Hantavirus pulmonary syndrome (HPS) is a life threatening disease transmitted by the rodent Oligo... more Hantavirus pulmonary syndrome (HPS) is a life threatening disease transmitted by the rodent Oligoryzomys longicaudatus in Chile. Hantavirus outbreaks are typically small and geographically confined. Several studies have estimated risk based on spatial and temporal distribution of cases in relation to climate and environmental variables, but few have considered climatological modeling of HPS incidence for monitoring and forecasting purposes. Monthly counts of confirmed HPS cases were obtained from the Chilean Ministry of Health for 2001-2012. There were an estimated 667 confirmed HPS cases. The data suggested a seasonal trend, which appeared to correlate with changes in climatological variables such as temperature, precipitation, and humidity. We considered several Auto Regressive Integrated Moving Average (ARIMA) time-series models and regression models with ARIMA errors with one or a combination of these climate variables as covariates. We adopted an information-theoretic approach to model ranking and selection. Data from 2001-2009 were used in fitting and data from January 2010 to December 2012 were used for one-step-ahead predictions. We focused on six models. In a baseline model, future HPS cases were forecasted from previous incidence; the other models included climate variables as covariates. The baseline model had a Corrected Akaike Information Criterion (AICc) of 444.98, and the top ranked model, which included precipitation, had an AICc of 437.62. Although the AICc of the top ranked model only provided a 1.65% improvement to the baseline AICc, the empirical support was 39 times stronger relative to the baseline model. Instead of choosing a single model, we present a set of candidate models that can be used in modeling and forecasting confirmed HPS cases in Chile. The models can be improved by using data at the regional level and easily extended to other countries with seasonal incidence of HPS.
PLoS Currents, 2013
&... more <b> </b> Hurricane Isaac made landfall in southeastern Louisiana in late August 2012, resulting in extensive storm surge and inland flooding. As the lead federal agency responsible for medical and public health response and recovery coordination, the Department of Health and Human Services (HHS) must have situational awareness to prepare for and address state and local requests for assistance following hurricanes. Both traditional and non-traditional data have been used to improve situational awareness in fields like disease surveillance and seismology. This study investigated whether non-traditional data (i.e., tweets and news reports) fill a void in traditional data reporting during hurricane response, as well as whether non-traditional data improve the timeliness for reporting identified HHS Essential Elements of Information (EEI). <b> </b> HHS EEIs provided the information collection guidance, and when the information indicated there was a potential public health threat, an event was identified and categorized within the larger scope of overall Hurricane Issac situational awareness. Tweets, news reports, press releases, and federal situation reports during Hurricane Isaac response were analyzed for information about EEIs. Data that pertained to the same EEI were linked together and given a unique event identification number to enable more detailed analysis of source content. Reports of sixteen unique events were examined for types of data sources reporting on the event and timeliness of the reports. <b> </b> Of these sixteen unique events identified, six were reported by only a single data source, four were reported by two data sources, four were reported by three data sources, and two were reported by four or more data sources. For five of the events where news tweets were one of multiple sources of information about an event, the tweet occurred prior to the news report, press release, local government\emergency management tweet, and federal situation report. In all circumstances where citizens were reporting along with other sources, the citizen tweet was the earliest notification of the event. <b> </b> Critical information is being shared by citizens, news organizations, and local government representatives. To have situational awareness for providing timely, life-saving public health and medical response following a hurricane, this study shows that non-traditional data sources should augment traditional data sources and can fill some of the gaps in traditional reporting. During a hurricane response where early event detection can save lives and reduce morbidity, tweets can provide a source of…
Canadian Medical Association Journal, 2010
New England Journal of Medicine, 2010
PLoS currents, 2015
The West Africa Ebola virus epidemic now appears to be coming to an end. In the proposed model, w... more The West Africa Ebola virus epidemic now appears to be coming to an end. In the proposed model, we simulate changes in population behavior that help to explain the observed transmission dynamics. We introduce an EVD transmission model accompanied by a model of social mobilization. The model was fit to Lofa County, Liberia through October 2014, using weekly counts of new cases reported by the US CDC. In simulation studies, we analyze the dynamics of the disease transmission with and without population behavior change, given the availability of beds in Ebola treatment units (ETUs) estimated from observed data. Only the model scenario that included individuals' behavioral change achieved a good fit to the observed case counts. Although the capacity of the Lofa County ETUs greatly increased in mid-August, our simulations show that the expansion was insufficient to alone control the outbreak. Modeling the entire outbreak without considering behavior change fit the data poorly, and ex...
Scientific reports, 2015
Challenges with alternative data sources for disease surveillance include differentiating the sig... more Challenges with alternative data sources for disease surveillance include differentiating the signal from the noise, and obtaining information from data constrained settings. For the latter, events such as increases in hospital traffic could serve as early indicators of social disruption resulting from disease. In this study, we evaluate the feasibility of using hospital parking lot traffic data extracted from high-resolution satellite imagery to augment public health disease surveillance in Chile, Argentina and Mexico. We used archived satellite imagery collected from January 2010 to May 2013 and data on the incidence of respiratory virus illnesses from the Pan American Health Organization as a reference. We developed dynamical Elastic Net multivariable linear regression models to estimate the incidence of respiratory virus illnesses using hospital traffic and assessed how to minimize the effects of noise on the models. We noted that predictions based on models fitted using a sampl...
Online Journal of Public Health Informatics, 2013
ABSTRACT Objective To introduce MoH+, HealthMap’s (HM) real-time feed of official government sour... more ABSTRACT Objective To introduce MoH+, HealthMap’s (HM) real-time feed of official government sources, and demonstrate its utility in comparing the timeliness of outbreak reporting between official and unofficial sources. Introduction Previous studies have documented significant lags in official reporting of outbreaks compared to unofficial reporting (1,2). MoH+ provides an additional tool to analyze this issue, with the unique advantage of actively gathering a wide range of streamlined official communication, including formal publications, online press releases, and social media updates. Methods Outbreaks reported by official sources were identified through MoH+ (healthmap.org/mohplus), which collects surveillance data published globally by ministries of health (MoH), other related ministries, government portals, government-affiliated organizations, and international governing bodies (Fig. 1). Reporting of these outbreaks was also identified in unofficial sources using various HM feeds including Google News, ProMED, and participatory surveillance feeds. Of the 109 outbreaks identified since May 2012, 65 were excluded as they started before data collection, 7 were excluded as they were not reported by unofficial sources, and 1 was excluded as it was a non-natural outbreak. For the remaining 36 outbreaks, the median difference in first date of report between official and unofficial sources was analyzed using a Wilcoxon sign rank test. Results Outbreak reporting in official sources lagged by a statistically significant median of 2 days (p=0.003). Among unofficial sources, online news most often (75%) was the fastest to report an outbreak, followed by ProMED (22%) and participatory surveillance (3%). Among official sources, national government affiliated institutes were most often (41%) the fastest, and repeatedly providing prompt outbreak reports were the US Centers for Disease Control and Prevention (CDC), Public Health Agency of Canada, Finnish Food Safety Authority, Health Protection Scotland, UK Health Protection Agency, and French Institute of Public Health Surveillance (FIPHS). Following such institutes were the European CDC (ECDC) with 22% of first reports of outbreaks; MoH’s (17%); and WHO (10%). There were 4 instances in which official sources reported before unofficial sources—3 by the ECDC and 1 by FIPHS. Conclusions Compared to the Chan study reporting a 16 day lag between first public communication and WHO Outbreak News (1) and the Mondor study reporting a 10 day lag between non-government and government sources (2), the present study shows a much condensed lag of 2 days between unofficial and official sources. Because the two earlier studies cover a much broader historical time frame, one explanation for the reduced lag time is increased adoption of online communication by official government agencies. However, despite such improvements in communication, the lag persists, pointing to the importance of using informal sources for outbreak surveillance. The present study was limited by small sample size, as the study is in its early stages. We will continue to gather data and all numbers will be updated in time for the presentation to reflect the larger database. Future directions of this study include characterization of official and unofficial reporting by region, language, disease, and source.
Clinical Infectious Diseases, 2014
Search query information from a clinician&amp... more Search query information from a clinician's database, UpToDate, is shown to predict influenza epidemics in the United States in a timely manner. Our results show that digital disease surveillance tools based on experts' databases may be able to provide an alternative, reliable, and stable signal for accurate predictions of influenza outbreaks.
Online Journal of Public Health Informatics, 2013
PloS one, 2012
A dearth of information obscures the true scale of the global illegal trade in wildlife. Herein, ... more A dearth of information obscures the true scale of the global illegal trade in wildlife. Herein, we introduce an automated web crawling surveillance system developed to monitor reports on illegally traded wildlife. A resource for enforcement officials as well as the general public, the freely available website, http://www.healthmap.org/wildlifetrade, provides a customizable visualization of worldwide reports on interceptions of illegally traded wildlife and wildlife products. From August 1, 2010 to July 31, 2011, publicly available English language illegal wildlife trade reports from official and unofficial sources were collected and categorized by location and species involved. During this interval, 858 illegal wildlife trade reports were collected from 89 countries. Countries with the highest number of reports included India (n = 146, 15.6%), the United States (n = 143, 15.3%), South Africa (n = 75, 8.0%), China (n = 41, 4.4%), and Vietnam (n = 37, 4.0%). Species reported as trade...
eLife, 2014
Ebola virus disease (EVD) is a complex zoonosis that is highly virulent in humans. The largest re... more Ebola virus disease (EVD) is a complex zoonosis that is highly virulent in humans. The largest recorded outbreak of EVD is ongoing in West Africa, outside of its previously reported and predicted niche. We assembled location data on all recorded zoonotic transmission to humans and Ebola virus infection in bats and primates (1976-2014). Using species distribution models, these occurrence data were paired with environmental covariates to predict a zoonotic transmission niche covering 22 countries across Central and West Africa. Vegetation, elevation, temperature, evapotranspiration, and suspected reservoir bat distributions define this relationship. At-risk areas are inhabited by 22 million people; however, the rarity of human outbreaks emphasises the very low probability of transmission to humans. Increasing population sizes and international connectivity by air since the first detection of EVD in 1976 suggest that the dynamics of human-to-human secondary transmission in contemporary...
PLoS Neglected Tropical Diseases, 2014
Hantavirus pulmonary syndrome (HPS) is a life threatening disease transmitted by the rodent Oligo... more Hantavirus pulmonary syndrome (HPS) is a life threatening disease transmitted by the rodent Oligoryzomys longicaudatus in Chile. Hantavirus outbreaks are typically small and geographically confined. Several studies have estimated risk based on spatial and temporal distribution of cases in relation to climate and environmental variables, but few have considered climatological modeling of HPS incidence for monitoring and forecasting purposes. Monthly counts of confirmed HPS cases were obtained from the Chilean Ministry of Health for 2001-2012. There were an estimated 667 confirmed HPS cases. The data suggested a seasonal trend, which appeared to correlate with changes in climatological variables such as temperature, precipitation, and humidity. We considered several Auto Regressive Integrated Moving Average (ARIMA) time-series models and regression models with ARIMA errors with one or a combination of these climate variables as covariates. We adopted an information-theoretic approach to model ranking and selection. Data from 2001-2009 were used in fitting and data from January 2010 to December 2012 were used for one-step-ahead predictions. We focused on six models. In a baseline model, future HPS cases were forecasted from previous incidence; the other models included climate variables as covariates. The baseline model had a Corrected Akaike Information Criterion (AICc) of 444.98, and the top ranked model, which included precipitation, had an AICc of 437.62. Although the AICc of the top ranked model only provided a 1.65% improvement to the baseline AICc, the empirical support was 39 times stronger relative to the baseline model. Instead of choosing a single model, we present a set of candidate models that can be used in modeling and forecasting confirmed HPS cases in Chile. The models can be improved by using data at the regional level and easily extended to other countries with seasonal incidence of HPS.
PLoS Currents, 2013
&... more <b> </b> Hurricane Isaac made landfall in southeastern Louisiana in late August 2012, resulting in extensive storm surge and inland flooding. As the lead federal agency responsible for medical and public health response and recovery coordination, the Department of Health and Human Services (HHS) must have situational awareness to prepare for and address state and local requests for assistance following hurricanes. Both traditional and non-traditional data have been used to improve situational awareness in fields like disease surveillance and seismology. This study investigated whether non-traditional data (i.e., tweets and news reports) fill a void in traditional data reporting during hurricane response, as well as whether non-traditional data improve the timeliness for reporting identified HHS Essential Elements of Information (EEI). <b> </b> HHS EEIs provided the information collection guidance, and when the information indicated there was a potential public health threat, an event was identified and categorized within the larger scope of overall Hurricane Issac situational awareness. Tweets, news reports, press releases, and federal situation reports during Hurricane Isaac response were analyzed for information about EEIs. Data that pertained to the same EEI were linked together and given a unique event identification number to enable more detailed analysis of source content. Reports of sixteen unique events were examined for types of data sources reporting on the event and timeliness of the reports. <b> </b> Of these sixteen unique events identified, six were reported by only a single data source, four were reported by two data sources, four were reported by three data sources, and two were reported by four or more data sources. For five of the events where news tweets were one of multiple sources of information about an event, the tweet occurred prior to the news report, press release, local government\emergency management tweet, and federal situation report. In all circumstances where citizens were reporting along with other sources, the citizen tweet was the earliest notification of the event. <b> </b> Critical information is being shared by citizens, news organizations, and local government representatives. To have situational awareness for providing timely, life-saving public health and medical response following a hurricane, this study shows that non-traditional data sources should augment traditional data sources and can fill some of the gaps in traditional reporting. During a hurricane response where early event detection can save lives and reduce morbidity, tweets can provide a source of…
Canadian Medical Association Journal, 2010
New England Journal of Medicine, 2010