scholarly journals Association between weather factors and dengue in Dhaka: a time-series analysis

2021 ◽  
Vol 39 (1) ◽  
pp. 43-49
Author(s):  
Shafia Shaheen
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Incidence Rate ◽  
Negative Binomial ◽  
Weather Data ◽  
Negative Binomial Regression Model ◽  
Weather Factors ◽  
Average Temperature ◽  
Series Analysis ◽  
Average Maximum

Background: There was an epidemic of dengue fever that happened  in Bangladesh  in the year of 2019. Temperature of this country has been raising which leads to changing in rainfall pattern. This study was aimed to investigate the relationship of weather factors and dengue incidence in Dhaka. Methods: A time series analysis was carried out by using 10 years weather data as average , maximum and minimum monthly temperature, average monthly humidity and average and cumulative monthly rainfall. Reported number of dengue cases was extracted from January 2009 to July 2019. Firstly, dengue incidence rate was  calculated. Correlation analysis and negative binomial regression model was developed. Results: Dengue incidence rate had sharp upward trend. Dengue incidence and mean, maximum and minimum average temperature showed statistically significant negative correlation at 3 months' lag. Highest incidence Rate Ratio (IRR) of dengue was found at minimum average temperature at 0 and I-month lag. Average humidity showed positive and significant correlation with dengue incidence at 0-month lag. Average and cumulative rainfall also showed negative and significant correlation only at 3-months lag period. Conclusion: Weather variability influences dengue incidence and the association between the weather factors are non­ linear and not consistent. So the study findings should be evaluated area basis with other local factors to develop early warning for dengue epidemic prediction. JOPSOM 2020; 39(1): 43-49

scholarly journals An interrupted time series analysis of the lockdown policies in India: a national-level analysis of COVID-19 incidence

2021 ◽  
Author(s):  
Winter M Thayer ◽  
Md Zabir Hasan ◽  
Prithvi Sankhla ◽  
Shivam Gupta
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Incidence Rate ◽  
Case Reports ◽  
National Level ◽  
Model Development ◽  
Interrupted Time Series ◽  
Interrupted Time Series Analysis ◽  
Additional Time ◽  
Series Analysis

Abstract India implemented a national mandatory lockdown policy (Lockdown 1.0) on 24 March 2020 in response to Coronavirus Disease 2019 (COVID-19). The policy was revised in three subsequent stages (Lockdown 2.0–4.0 between 15 April to 18 May 2020), and restrictions were lifted (Unlockdown 1.0) on 1 June 2020. This study evaluated the effect of lockdown policy on the COVID-19 incidence rate at the national level to inform policy response for this and future pandemics. We conducted an interrupted time series analysis with a segmented regression model using publicly available data on daily reported new COVID-19 cases between 2 March 2020 and 1 September 2020. National-level data from Google Community Mobility Reports during this timeframe were also used in model development and robustness checks. Results showed an 8% [95% confidence interval (CI) = 6–9%] reduction in the change in incidence rate per day after Lockdown 1.0 compared to prior to the Lockdown order, with an additional reduction of 3% (95% CI = 2–3%) after Lockdown 4.0, suggesting an 11% (95% CI = 9–12%) reduction in the change in COVID-19 incidence after Lockdown 4.0 compared to the period before Lockdown 1.0. Uptake of the lockdown policy is indicated by decreased mobility and attenuation of the increasing incidence of COVID-19. The increasing rate of incident case reports in India was attenuated after the lockdown policy was implemented compared to before, and this reduction was maintained after the restrictions were eased, suggesting that the policy helped to ‘flatten the curve’ and buy additional time for pandemic preparedness, response and recovery.

scholarly journals Incidence of hip and knee replacement in patients with rheumatoid arthritis following the introduction of biological DMARDs: an interrupted time-series analysis using nationwide Danish healthcare registers

2017 ◽  
Vol 77 (5) ◽  
pp. 684-689 ◽  
Author(s):  
René Lindholm Cordtz ◽  
Samuel Hawley ◽  
Daniel Prieto-Alhambra ◽  
Pil Højgaard ◽  
Kristian Zobbe ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Time Series ◽  
Time Series Analysis ◽  
Incidence Rate ◽  
Interrupted Time Series ◽  
Incidence Rates ◽  
Interrupted Time Series Analysis ◽  
Series Analysis ◽  
National Patient ◽  
The Impact

ObjectivesTo study the impact of the introduction of biological disease-modifying anti-rheumatic drugs (bDMARDs) and associated rheumatoid arthritis (RA) management guidelines on the incidence of total hip (THR) and knee replacements (TKR) in Denmark.MethodsNationwide register-based cohort and interrupted time-series analysis. Patients with incident RA between 1996 and 2011 were identified in the Danish National Patient Register. Patients with RA were matched on age, sex and municipality with up to 10 general population comparators (GPCs). Standardised 5-year incidence rates of THR and TKR per 1000 person-years were calculated for patients with RA and GPCs in 6-month periods. Levels and trends in the pre-bDMARD (1996–2001) were compared with the bDMARD era (2003–2016) using segmented linear regression interrupted by a 1-year lag period (2002).ResultsWe identified 30 404 patients with incident RA and 297 916 GPCs. In 1996, the incidence rate of THR and TKR was 8.72 and 5.87, respectively, among patients with RA, and 2.89 and 0.42 in GPCs. From 1996 to 2016, the incidence rate of THR decreased among patients with RA, but increased among GPCs. Among patients with RA, the incidence rate of TKR increased from 1996 to 2001, but started to decrease from 2003 and throughout the bDMARD era. The incidence of TKR increased among GPCs from 1996 to 2016.ConclusionWe report that the incidence rate of THR and TKR was 3-fold and 14-fold higher, respectively among patients with RA compared with GPCs in 1996. In patients with RA, introduction of bDMARDs was associated with a decreasing incidence rate of TKR, whereas the incidence of THR had started to decrease before bDMARD introduction.

scholarly journals Impact of the Introduction of Rotavirus Vaccine on Hospital Admissions for Diarrhea Among Children in Kenya: A Controlled Interrupted Time-Series Analysis

2019 ◽  
Vol 70 (11) ◽  
pp. 2306-2313 ◽  
Author(s):  
Grieven P Otieno ◽  
Christian Bottomley ◽  
Sammy Khagayi ◽  
Ifedayo Adetifa ◽  
Mwanajuma Ngama ◽  
...  
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Negative Binomial ◽  
Substantial Reduction ◽  
Interrupted Time Series ◽  
Rotavirus Vaccine ◽  
Interrupted Time Series Analysis ◽  
Control Series ◽  
Vaccine Introduction ◽  
Series Analysis

Abstract Background Monovalent rotavirus vaccine, Rotarix (GlaxoSmithKline), was introduced in Kenya in July 2014 and is recommended to infants as oral doses at ages 6 and 10 weeks. A multisite study was established in 2 population-based surveillance sites to evaluate vaccine impact on the incidence of rotavirus-associated hospitalizations (RVHs). Methods Hospital-based surveillance was conducted from January 2010 to June 2017 for acute diarrhea hospitalizations among children aged <5 years in 2 health facilities in Kenya. A controlled interrupted time-series analysis was undertaken to compare RVH pre– and post–vaccine introduction using rotavirus-negative cases as a control series. The change in incidence post–vaccine introduction was estimated from a negative binomial model that adjusted for secular trend, seasonality, and multiple health worker industrial actions (strikes). Results Between January 2010 and June 2017 there were 1513 and 1652 diarrhea hospitalizations in Kilifi and Siaya; among those tested for rotavirus, 28% (315/1142) and 23% (197/877) were positive, respectively. There was a 57% (95% confidence interval [CI], 8–80%) reduction in RVHs observed in the first year post–vaccine introduction in Kilifi and a 59% (95% CI, 20–79%) reduction in Siaya. In the second year, RVHs decreased further at both sites, 80% (95% CI, 46–93%) reduction in Kilifi and 82% reduction in Siaya (95% CI. 61–92%); this reduction was sustained at both sites into the third year. Conclusions A substantial reduction in RVHs and all-cause diarrhea was observed in 2 demographic surveillance sites in Kenya within 3 years of vaccine introduction.

scholarly journals Trends in inpatient care for psychiatric disorders in NHS hospitals across England, 1998/99–2019/20: an observational time series analysis

2021 ◽  
Author(s):  
Michelle Degli Esposti ◽  
Hisham Ziauddeen ◽  
Lucy Bowes ◽  
Aaron Reeves ◽  
Adam M. Chekroud ◽  
...  
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Psychiatric Disorders ◽  
Regression Models ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Admission Rates ◽  
Series Analysis ◽  
Binomial Regression ◽  
Bed Days

Abstract Purpose It is unclear how hospitals are responding to the mental health needs of the population in England, against a backdrop of diminishing resources. We aimed to document patterns in hospital activity by psychiatric disorder and how these have changed over the last 22 years. Methods In this observational time series analysis, we used routinely collected data on all NHS hospitals in England from 1998/99 to 2019/20. Trends in hospital admissions and bed days for psychiatric disorders were smoothed using negative binomial regression models with year as the exposure and rates (per 1000 person-years) as the outcome. When linear trends were not appropriate, we fitted segmented negative binomial regression models with one change-point. We stratified by gender and age group [children (0–14 years); adults (15 years +)]. Results Hospital admission rates and bed days for all psychiatric disorders decreased by 28.4 and 38.3%, respectively. Trends were not uniform across psychiatric disorders or age groups. Admission rates mainly decreased over time, except for anxiety and eating disorders which doubled over the 22-year period, significantly increasing by 2.9% (AAPC = 2.88; 95% CI: 2.61–3.16; p < 0.001) and 3.4% (AAPC = 3.44; 95% CI: 3.04–3.85; p < 0.001) each year. Inpatient hospital activity among children showed more increasing and pronounced trends than adults, including an increase of 212.9% for depression, despite a 63.8% reduction for adults with depression during the same period. Conclusion In the last 22 years, there have been overall reductions in hospital activity for psychiatric disorders. However, some disorders showed pronounced increases, pointing to areas of growing need for inpatient psychiatric care, especially among children.

scholarly journals Impact of free maternity policies in Kenya: an interrupted time-series analysis

2021 ◽  
Vol 6 (6) ◽  
pp. e003649
Author(s):  
Stacey Orangi ◽  
Angela Kairu ◽  
Lucas Malla ◽  
Joanne Ondera ◽  
Boniface Mbuthia ◽  
...  
Keyword(s):  
Time Series ◽  
Maternal Health ◽  
Time Series Analysis ◽  
Negative Binomial ◽  
Health Information System ◽  
Interrupted Time Series ◽  
Interrupted Time Series Analysis ◽  
Faith Based ◽  
Public Facilities ◽  
Series Analysis

BackgroundUser fees have been reported to limit access to services and increase inequities. As a result, Kenya introduced a free maternity policy in all public facilities in 2013. Subsequently in 2017, the policy was revised to the Linda Mama programme to expand access to private sector, expand the benefit package and change its management.MethodsAn interrupted time-series analysis on facility deliveries, antenatal care (ANC) and postnatal care (PNC) visits data between 2012 and 2019 was used to determine the effect of the two free maternity policies. These data were from 5419 public and 305 private and faith-based facilities across all counties, with data sourced from the health information system. A segmented negative binomial regression with seasonality accounted for, was used to determine the level (immediate) effect and trend (month-on-month) effect of the policies.ResultsThe 2013 free-maternity policy led to a 19.6% and 28.9% level increase in normal deliveries and caesarean sections, respectively, in public facilities. There was also a 1.4% trend decrease in caesarean sections in public facilities. A level decrease followed by a trend increase in PNC visits was reported in public facilities. For private and faith-based facilities, there was a level decrease in caesarean sections and ANC visits followed by a trend increase in caeserean sections following the 2013 policy.Furthermore, the 2017 Linda Mama programme showed a level decrease then a trend increase in PNC visits and a 1.1% trend decrease in caesarean sections in public facilities. In private and faith-based facilities, there was a reported level decrease in normal deliveries and caesarean sections and a trend increase in caesarean sections.ConclusionThe free maternity policies show mixed effects in increasing access to maternal health services. Emphasis on other accessibility barriers and service delivery challenges alongside user fee removal policies should be addressed to realise maximum benefits in maternal health utilisation.

Effects of weather variability on infectious gastroenteritis

2009 ◽  
Vol 138 (2) ◽  
pp. 236-243 ◽  
Author(s):  
D. ONOZUKA ◽  
M. HASHIZUME ◽  
A. HAGIHARA
Keyword(s):  
Time Series ◽  
Relative Humidity ◽  
Time Series Analysis ◽  
Gastrointestinal Disease ◽  
Confounding Factors ◽  
Weather Variability ◽  
Average Temperature ◽  
Series Analysis ◽  
Infectious Gastroenteritis

SUMMARYAlthough multiple combinations of weather variability may contribute to an increased incidence of infectious gastrointestinal disease, few studies have investigated the association between weather variability and cases of infectious gastroenteritis. We acquired data for infectious gastroenteritis cases and weather variability in Fukuoka, Japan, from 1999 to 2007 and used time-series analysis to assess the effects of weather variability on infectious gastroenteritis cases, adjusting for confounding factors. In total, 422 176 infectious gastroenteritis cases were reported during the 9-year study period. The weekly number of infectious gastroenteritis cases increased by 7·7% (95% CI 4·6–10·8) for every 1°C increase in the average temperature and by 2·3% (95% CI 1·4–3·1) for every 1% decrease in relative humidity. From 1999 to 2007, infectious gastroenteritis cases increased significantly with increased average temperature and decreased relative humidity in Fukuoka, Japan.

Abstract 12127: The Effect of Daylight Savings Time Transitions on the Incidence of Out-of-Hospital Cardiac Arrest: An Interrupted Time Series Analysis

Circulation ◽  
2021 ◽  
Vol 144 (Suppl_2) ◽  
Author(s):  
Jack Hook ◽  
Karen L Smith ◽  
Emily Andrew ◽  
Jocasta Ball ◽  
Ziad Nehme
Keyword(s):  
Time Series ◽  
Cardiac Arrest ◽  
Time Series Analysis ◽  
Negative Binomial ◽  
Interrupted Time Series ◽  
Cumulative Effects ◽  
Interrupted Time Series Analysis ◽  
Series Analysis ◽  
Increased Risk ◽  
Hospital Cardiac Arrest

Introduction: Many studies have reported increases in the risk of acute cardiovascular events following daylight savings time (DST) transitions. We sought to investigate the effect of DST transitions on the incidence of out-of-hospital cardiac arrest (OHCA) in Victoria, Australia. Methods: Between January 2000 and December 2020, we performed an interrupted time series analysis of the daily number of OHCA cases of medical etiology from the Victorian Ambulance Cardiac Arrest Registry. The effect of DST transition on OHCA incidence was estimated using negative binomial models and reported as either ‘immediate’ or ‘cumulative’ effects. Immediate effects were the average effects observed on the day of DST transition or each of the 6 days after DST transition. Cumulative effects were the sum of the average effects up to 6 days after the day of DST transition. Models were adjusted for population growth, temporal trends, and public holidays. Results: A total of 89,409 adult OHCA of medical etiology were included. Following the spring DST transition (i.e. shorter day), there was an immediate 13% (IRR 1.13, 95% CI: 1.02, 1.25; p=0.02) increased risk of OHCA on the day of transition (Sunday) and the cumulative risk of OHCA remained higher over the first 2 days (IRR 1.17, 95% CI: 1.02, 1.34; p=0.03) compared to non-transitional days. Following the autumn (fall) DST transition (i.e. longer day), there was a significant lagged effect on the Tuesday following transition, with a 12% (IRR 0.88, 95% CI: 0.77, 0.99; p=0.04) reduced risk of OHCA. The autumn (fall) DST transition also showed a cumulative effect on OHCA incidence, with a 30% (IRR 0.70, 95% CI: 0.51, 0.96; p=0.03) reduction in the incidence of OHCA by the end of the transitional week. Subgroups aged > 65 years and cases with initial non-shockable rhythms were most vulnerable to DST transitions. Conclusions: This study showed that there is a modest increased risk of OHCA in the 2 days following the spring DST transition and a decreased risk of OHCA in the week following the autumn DST transition. These findings should promote further research exploring strategies to reduce the risk of OHCA in vulnerable populations.

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