How would Widespread Community Transmission of Covid-19 in Sri Lanka look like? A Population-based Prediction

Abstract Covid-19 is a viral disease which has briskly invaded the globe, Sri Lanka being no exception. If community transmission of Covid-19 occurs, it will have serious demands on Sri Lanka’s free health care system. Objective of this study was to simulate the widespread community transmission of Covid-19 in Sri Lanka. We used the Susceptibility, Infected and Removed (SIR) model through the Penn State University CHIME Model incorporated to ArcGIS Pro. We simulated introduction of one case of Covid-19 to each of the 26 health districts and ran the model for 365 days. During simulated scenario, the number patients requiring admissions, ICU care and mechanical ventilation will peak at 1942, 583 and 388 per day respectively around 213 days from the onset of widespread community transmission. The cumulative number of cases needing admission, ICU care and ventilation will be 245,916, 73,775 and 49,183 after 365 days. Colombo and Gampaha districts will report the highest number of daily total numbers of hospitalized cases, each which will be over 1680. Health authorities must be ready for the worst-case scenarios of the Covid-19 outbreak to sustain public health response to reduce morbidity and mortality.

Download Full-text

How would Widespread Community Transmission of Covid-19 in Sri Lanka look like? A Population-based Simulation

International Journal of Community Resilience ◽

10.51595/injcr/11111118 ◽

2021 ◽

Author(s):

NWANY Wijesekara ◽

HDB Herath ◽

KALC Kodituwakku ◽

HMMNK Herath ◽

BAMP Bulathsinghe ◽

...

Keyword(s):

Sri Lanka ◽

Sir Model ◽

Population Based ◽

Cumulative Number ◽

State University ◽

Worst Case ◽

Health Authorities ◽

Number Of Patients ◽

Penn State ◽

Community Transmission

Abstract Widespread community transmission of Covid-19 can overwhelm the capacity of health systems; Sri Lanka is no exception. We simulated the widespread community transmission of Covid-19 in Sri Lanka, using the Susceptibility, Infected and Removed (SIR) model through the Penn State University CHIME Model incorporated to ArcGIS Pro, by introducing one case of Covid-19 to the current population in each of the 26 health districts and running the model for 365 days. The simulation revealed that the number of patients requiring admissions, ICU care, and mechanical ventilation would peak at 1942, 583, and 388 per day, respectively, around 213 days from the onset. The cumulative number of cases needing admission, ICU care, and ventilation will be 245,916, 73,775, and 49,183 after 365 days. Colombo and Gampaha districts will report the highest number of daily total numbers of hospitalized cases over 1680. Health authorities can use the results of such simulations to prepare to face the worst-case scenarios of the Covid-19 outbreak to minimize morbidity and mortality. Keywords: Covid-19, Community Transmission, SIR Model, CHIME, Outbreak, Simulation, Prediction

Download Full-text

Developing a Digital Solution for Dengue Through Epihack: Qualitative Evaluation Study of a Five-Day Health Hackathon in Sri Lanka

JMIR Formative Research ◽

10.2196/11555 ◽

2019 ◽

Vol 3 (3) ◽

pp. e11555 ◽

Cited By ~ 1

Author(s):

Chitra Panchapakesan ◽

Anita Sheldenkar ◽

Prasad Wimalaratne ◽

Ruwan Wijayamuni ◽

May Oo Lwin

Keyword(s):

Sri Lanka ◽

Expert Knowledge ◽

Qualitative Evaluation ◽

Viral Disease ◽

Evaluation Study ◽

Good Communication ◽

Participant Engagement ◽

Health Authorities ◽

Digital Surveillance ◽

New Ideas

Background Dengue is a mosquito-borne viral disease that has increasingly affected Sri Lanka in recent years. To address this issue, dengue surveillance through increasingly prevalent digital surveillance applications has been suggested for use by health authorities and the general public. Epihack Sri Lanka was a 5-day hackathon event organized to develop a digital dengue surveillance tool. Objective The goal of the research was to examine the effectiveness of a collaborative hackathon that brought together information technology (IT) and health experts from around the globe to develop a solution to the dengue pandemic in Sri Lanka. Methods Ethnographic observation and qualitative informal interviews were conducted with 58 attendees from 11 countries over the 5-day Epihack to identify the main factors that influence a collaborative hackathon. Interviews were transcribed and coded based on grounded theory. Results Three major themes were identified during the Epihack Sri Lanka event: engagement, communication, and current disease environment. Unlike other hackathons, Epihack had no winners or prizes and was collaborative rather than competitive, which worked well in formulating a variety of ideas and bringing together volunteers with a sense of civic duty to improve public health. Having health and IT experts work together concurrently was received positively and considered highly beneficial to the development of the product. Participants were overall very satisfied with the event, although they thought it could have been longer. Communication issues and cultural differences were observed but continued to decrease as the event progressed. This was found to be extremely important to the efficiency of the event, which highlighted the benefit of team-bonding exercises. Bringing expert knowledge and examples of systems from around the world benefited the creation of new ideas. However, developing a system that can adapt and cater to the local disease environment is important in successfully developing the concepts. Conclusions Epihack Sri Lanka was successful in bringing together health and IT experts to develop a digital solution for dengue surveillance. The collaborative format achieved a variety of fruitful ideas and may lead to more hackathons working in this way in the future. Good communication, participant engagement, and stakeholder interest with adaptation of ideas to complement the current environment are vital to achieve the goals of the event.

Download Full-text

Fuzzy Multidimensional Model to Cluster Dengue Risk in Sri Lanka

BioMed Research International ◽

10.1155/2020/2420948 ◽

2020 ◽

Vol 2020 ◽

pp. 1-16

Author(s):

I. T. S. Piyatilake ◽

S. S. N. Perera

Keyword(s):

Sri Lanka ◽

Dengue Fever ◽

Hot Spots ◽

Dominant Role ◽

Geometric Mean ◽

Viral Disease ◽

Annual Number ◽

Administrative District ◽

Health Authorities ◽

New Situation

Dengue is the world’s rapidly transmitting mosquito-borne viral disease. It is mostly found in subtropical countries in the world. The annual number of global deaths caused by dengue fever is about 25,000. The Sri Lanka dengue situation is also not different to other countries. In the year 2019, dengue fever caused 120 deaths in Sri Lanka. Most of these deaths were reported from the main administrative district Colombo. Health authorities have to pay their attention to control this new situation. Therefore, identifying the hot spots in the country and implementing necessary actions to control the disease is an important task. This study aims to develop a clustering technique to identify the dengue hot spots in Sri Lanka. Suitable risk factors are identified using expert ideas and reviewing available literature. The weights are derived using Chang’s extent method. These weights are used to prioritize the factors associated with dengue. Using the geometric mean, the interaction between the triggering variable and other variables is calculated. According to the interaction matrices, five dengue risk clusters are identified. It is found that high population movement in the area plays a dominant role to transmit the disease to other areas. Most of the districts in Sri Lanka will reach to moderate risk cluster in the year 2022.

Download Full-text

Two-Way Contact Network Modeling for Identifying the Route of COVID-19 Community Transmission

Informatics ◽

10.3390/informatics8020022 ◽

2021 ◽

Vol 8 (2) ◽

pp. 22

Author(s):

Sung Jin Lee ◽

Sang Eun Lee ◽

Ji-On Kim ◽

Gi Bum Kim

Keyword(s):

Simulated Data ◽

Contact Network ◽

Transmission Route ◽

Time Step ◽

Source Of Infection ◽

Health Authorities ◽

Control And Prevention ◽

Community Transmission ◽

Centrality Analysis ◽

Selection Of

In this study, we address the problem originated from the fact that “The Corona 19 Epidemiological Research Support System,” developed by the Korea Centers for Disease Control and Prevention, is limited to analyzing the Global Positioning System (GPS) information of the confirmed COVID-19 cases alone. Consequently, we study a method that the authority predicts the transmission route of COVID-19 between visitors in the community from a spatiotemporal perspective. This method models a contact network around the first confirmed case, allowing the health authorities to conduct tests on visitors after an outbreak of COVID-19 in the community. After securing the GPS data of community visitors, it traces back to the past from the time the first confirmed case occurred and creates contact clusters at each time step. This is different from other researches that focus on identifying the movement paths of confirmed patients by forward tracing. The proposed method creates the contact network by assigning weights to each contact cluster based on the degree of proximity between contacts. Identifying the source of infection in the contact network can make us predict the transmission route between the first confirmed case and the source of infection and classify the contacts on the transmission route. In this experiment, we used 64,073 simulated data for 100 people and extracted the transmission route and a top 10 list for centrality analysis. The contacts on the route path can be quickly designated as a priority for COVID-19 testing. In addition, it is possible for the authority to extract the subjects with high influence from the centrality theory and use them for additional COVID-19 epidemic investigation that requires urgency. This model is expected to be used in the epidemic investigation requiring the quick selection of close contacts.

Download Full-text

The prevalence, predictors and associations of hypertension in Sri Lanka: a cross-sectional population based national survey

Clinical and Experimental Hypertension ◽

10.3109/10641963.2013.863321 ◽

2014 ◽

Vol 36 (7) ◽

pp. 484-491 ◽

Cited By ~ 27

Author(s):

Prasad Katulanda ◽

Priyanga Ranasinghe ◽

Ranil Jayawardena ◽

Godwin R. Constantine ◽

M. H. Rezvi Sheriff ◽

...

Keyword(s):

Sri Lanka ◽

National Survey ◽

Population Based ◽

Cross Sectional

Download Full-text

Abstract P249: Incident Sleep-Disordered Breathing is Associated with Obesity: Penn State Child Cohort

Circulation ◽

10.1161/circ.127.suppl_12.ap249 ◽

2013 ◽

Vol 127 (suppl_12) ◽

Author(s):

Edward O Bixler ◽

Alexandros N Vgontzas ◽

Duanping Liao ◽

Susan Calhoun ◽

Julio Fernandez-Mendoza ◽

...

Keyword(s):

Risk Factors ◽

Logistic Regression ◽

Sleep Disordered Breathing ◽

Population Sample ◽

Population Based ◽

Penn State ◽

Potential Risk Factors ◽

State Child ◽

Disordered Breathing

Objectives: To study the epidemiology of sleep-disordered breathing (SDB) in adolescents, which has received little attention. Methods: The Penn State Child Cohort (PSCC) is a representative general population sample of 700 children aged 5-12 years. Our preliminary results are based on an average 8 year follow up of the initial 300 prospective subjects (~43%) from this ongoing cohort study. A logistic regression was used to assess the association between potential risk factors and incident SDB. Results: The mean age at the 8-year follow up examination was 17.2 ± 0.1 years, with an average BMI percentile of 66.6 ± 1.6 and 56.5% boys. At baseline 1.5% of this subsample had SDB, defined by Apnea Hypopnia Index (AHI > 5 /hour). Surprisingly, there was no persistence of SDB. Eight-year incident SDB was 10.5%. The average AHI in those with incident SDB was 12.7 with a maximum of 92.4. Incident SDB was similar for girls (7.8%) and boys (12.7%). Those with SDB were older than those without (18.7 vs 17.0 years, P<0.001) and girls with SDB were older than boys with SDB (20.0 vs 18.0 years, P=0.002). Those with incident SDB tended to have a greater change in BMI percentile (8.2 vs 1.8, P = 0.143) during the follow up and slightly higher minority representation (25.8% vs 21.9%, P=0.655). A logistic regression model identified three variables that were associated with incident SDB, controlling for baseline AHI: age (OR = 1.5 (1.3, 1.9) P<0.001), male (OR= 2.5 (1.11,10.00) P=0.021), and [[Unable to Display Character: ∆]]BMIPCT (OR=1.2(1.02, 1.5) P=0.032). Conclusion: In this population based sample of adolescents, the 8-year incidence of SDB was high (10.5%), whereas childhood SDB did not persist into adolescence. Further, the results indicate that risk factors for incident SDB in adolescents are age, male and the development of obesity.

Download Full-text

A Nationwide Registry-Based Study on Mortality Due to Rare Congenital Anomalies

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph15081715 ◽

2018 ◽

Vol 15 (8) ◽

pp. 1715 ◽

Cited By ~ 3

Author(s):

Verónica Alonso-Ferreira ◽

Germán Sánchez-Díaz ◽

Ana Villaverde-Hueso ◽

Manuel Posada de la Paz ◽

Eva Bermejo-Sánchez

Keyword(s):

Congenital Anomalies ◽

Time Trends ◽

Mortality Rates ◽

Population Based ◽

Geographical Differences ◽

Disease Epidemiology ◽

Risk Of Death ◽

Health Authorities ◽

Icd 10 ◽

Related Mortality

This study aimed to analyse population-based mortality attributed to rare congenital anomalies (CAs) and assess the associated time trends and geographical differences in Spain. Data on CA-related deaths were sourced from annual mortality databases kept by the National Statistics Institute of Spain (1999–2013). Based on the ICD-10, only CAs corresponding to rare diseases definition were included in this study. Annual age-adjusted mortality rates were calculated and time trends were evaluated by joinpoint regression analysis. Geographical differences were assessed using standardised mortality ratios and cluster detection. A total of 13,660 rare-CA-related deaths (53.4% males) were identified in the study period. Annual age-adjusted mortality rates decreased by an average of −5.2% (−5.5% males, −4.8% females, p < 0.001). Geographical analysis showed a higher risk of rare-CA-related mortality in regions largely located in the south of the country. Despite their limitations, mortality statistics are essential and useful tools for enhancing knowledge of rare disease epidemiology and, by extension, for designing and targeting public health actions. Monitoring rare-CA-related mortality in Spain has shown a 15-year decline and geographical differences in the risk of death, all of which might well be taken into account by the health authorities in order to ensure equality and equity, and to adopt appropriate preventive measures.

Download Full-text

Early introductions and community transmission of SARS-CoV-2 variant B.1.1.7 in the United States

10.1101/2021.02.10.21251540 ◽

2021 ◽

Author(s):

Tara Alpert ◽

Erica Lasek-Nesselquist ◽

Anderson F. Brito ◽

Andrew L. Valesano ◽

Jessica Rothman ◽

...

Keyword(s):

Public Health ◽

United States ◽

New York ◽

Diagnostic Testing ◽

The United States ◽

International Travel ◽

Health Concern ◽

Public Health Response ◽

Community Transmission ◽

The Uk

SummaryThe emergence and spread of SARS-CoV-2 lineage B.1.1.7, first detected in the United Kingdom, has become a national public health concern in the United States because of its increased transmissibility. Over 500 COVID-19 cases associated with this variant have been detected since December 2020, but its local establishment and pathways of spread are relatively unknown. Using travel, genomic, and diagnostic testing data, we highlight the primary ports of entry for B.1.1.7 in the US and locations of possible underreporting of B.1.1.7 cases. New York, which receives the most international travel from the UK, is likely one of the key hubs for introductions and domestic spread. Finally, we provide evidence for increased community transmission in several states. Thus, genomic surveillance for B.1.1.7 and other variants urgently needs to be enhanced to better inform the public health response.

Download Full-text

Trends in initiation of direct oral anticoagulant therapies for atrial fibrillation in a national population-based cross-sectional study in the French health insurance databases

BMJ Open ◽

10.1136/bmjopen-2017-018180 ◽

2018 ◽

Vol 8 (3) ◽

pp. e018180 ◽

Cited By ~ 23

Author(s):

Laetitia Huiart ◽

Cyril Ferdynus ◽

Christel Renoux ◽

Amélie Beaugrand ◽

Sophie Lafarge ◽

...

Keyword(s):

Atrial Fibrillation ◽

Multivariate Analysis ◽

National Health ◽

Oral Anticoagulant ◽

Vitamin K Antagonists ◽

Population Based ◽

Administrative Database ◽

Direct Oral Anticoagulant ◽

Health Authorities ◽

First Choice

ObjectiveUnlike several other national health agencies, French health authorities recommended that the newer direct oral anticoagulant (DOAC) agents only be prescribed as second choice for the treatment of newly diagnosed non-valvular atrial fibrillation (NVAF), with vitamin K antagonists (VKA) remaining the first choice. We investigated the patterns of use of DOACs versus VKA in the treatment of NVAF in France over the first 5 years of DOAC availability. We also identified the changes in patient characteristics of those who initiated DOAC treatment over this time period.MethodsBased on the French National Health Administrative Database, we constituted a population-based cohort of all patients who were newly treated for NVAF between January 2011 and December 2015. Trends in drug use were described as the percentage of patients initiating each drug at the time of treatment initiation. A multivariate analysis using logistic regression model was performed to identify independent sociodemographic and clinical predictors of initial anticoagulant choice.ResultsThe cohort comprised 814 446 patients who had received a new anticoagulant treatment for NVAF. The proportion of patients using DOACs as initial anticoagulant therapy reached 54% 3 months after the Health Ministry approved the reimbursement of dabigatran for NVAF, and 61% by the end of 2015, versus VKA use. In the multivariate analysis, we found that DOAC initiators were younger and healthier overall than VKA initiators, and this tendency was reinforced over the 2011–2014 period. DOACs were more frequently prescribed by cardiologists in 2012 and after (adjusted OR in 2012: 2.47; 95% CI 2.40 to 2.54).ConclusionDespite recommendations from health authorities, DOACs have been rapidly and massively adopted as initial therapy for NVAF in France. Observational studies should account for the fact that patients selected to initiate DOAC treatment are healthier overall, as failure to do so may bias the risk–benefit assessment of DOACs.

Download Full-text

Abstract P200: The Circadian Pattern of Cardiac Autonomic Modulation and its Correlates in Adolescents- Penn State Child Cohort (PSCC) Study

Circulation ◽

10.1161/circ.129.suppl_1.p200 ◽

2014 ◽

Vol 129 (suppl_1) ◽

Author(s):

Sol M Rodriguez-Colon ◽

Fan He ◽

Edward O Bixler ◽

Julio Fernandez-Mendoza ◽

Susan Calhoun ◽

...

Keyword(s):

Heart Rate ◽

Low Frequency ◽

Population Based ◽

Autonomic Modulation ◽

Circadian Pattern ◽

Late Afternoon ◽

Cardiac Autonomic Modulation ◽

Penn State ◽

State Child ◽

The Mean

Objective: To examine the circadian pattern of cardiac autonomic modulation (CAM) and its correlates in a population-based sample of adolescents. Methods: We used the data from 400 adolescents who completed the follow up exam in the PSCC study. CAM was assessed by heart rate variability (HRV) analysis of beat-to-beat normal R-R intervals from a 24-hour (7:00 PM to 7:00 PM) ECG, on a 30-minute basis (48 segments/person). The HRV indices included frequency domain: [high and low frequency powers (HF, LF), and LF/HF ratio] and time domain: [standard deviation of normal RRs (SDNN), and the square root of the mean squared difference of successive normal RRs (RMSSD), and heart rate (HR)]. We used a cosine periodic model to estimate each participant’s circadian parameters: mean (M), amplitude (Â), and crescent time (θ). We then used mixed-effects models to calculate group level circadian pattern as the overall M, Â of the oscillation, and θ of the highest oscillation. Results: The mean age was 16.9 yrs (SD=2.2), with 54% male and 77% white. The mean BMI percentile is 61, with 16% were obese (BMI percentile ≥ 95). Overall, the parasympathetic modulation gradually increases from late afternoon throughout the evening, and reaches the peak amplitude around 3:00 AM, at which it gradually decrease throughout most of the daytime until late afternoon. The age, sex and race showed varying differences on the CAM circadian parameters. In contrast, obesity in adolescents had adverse effects on all three circadian parameters. Using HF (a reliable index of parasympathetic modulation) as an example, the circadian pattern of the entire sample, and stratified by obesity are shown in Figure 1. Conclusion: Circadian pattern of CAM can be quantified by three cosine parameters (M, Â, and θ). Obesity in adolescents is already associated with a CAM profile indicative of sympathetic overflow and reduced parasympathetic modulation, at all levels of the CAM circadian rhythm.

Download Full-text