11 research outputs found
The epidemiology of dengue outbreaks in 2016 and 2017 in Ouagadougou, Burkina Faso.
BACKGROUND: Dengue is prevalent in as many as 128 countries with more than 100 million clinical episodes reported annually and four billion people estimated to be at risk. While dengue fever is systematically diagnosed in large parts of Asia and South America, the disease burden in Africa is less well investigated. This report describes two consecutive dengue outbreaks in Ouagadougou, Burkina Faso in 2016 and 2017. METHODS: Blood samples of febrile patients received at Schiphra laboratory in Ouagadougou, Burkina Faso, were screened for dengue infection using SD Bioline Dengue Duo rapid diagnostic test kits (Standard Diagnostics, Suwon, Republic of Korea). RESULTS: A total of 1,397 and 1,882 cases were reported by a single laboratory in 2016 and 2017, respectively. Most cases were at least 15 years of age and the results corroborated reports from WHO indicating the circulation of three dengue virus serotypes in Burkina Faso. CONCLUSION: This study complements data from other, simultaneously conducted surveillance efforts, and indicates that the dengue disease burden might be underestimated in sub-Saharan African nations. Dengue surveillance should be enhanced in African settings to determine the burden more accurately, and accelerated efforts towards a dengue vaccine should be put in place
Projections of Excess Mortality Related to Diurnal Temperature Range Under Climate Change Scenarios: a multi-country modelling study
Various retrospective studies have reported on the increase of mortality risk due to higher diurnal temperature range (DTR). This study projects the effect of DTR on future mortality across 445 communities in 20 countries and regions
์ค์ฌ์ ์จ๋ ๋ฐ ๊ฐ์๋์ ์ฐ๊ด์ฑ. ์ฌํ๋ผ ์ฌ๋ง ์ด๋จ์ ์ํ๋ฆฌ์นด 10๊ฐ ๊ตญ๊ฐ๋ค์ ๋์์ผ๋ก.
ํ์๋
ผ๋ฌธ (์์ฌ) -- ์์ธ๋ํ๊ต ๋ํ์ : ๋ณด๊ฑด๋ํ์ ๋ณด๊ฑดํ๊ณผ, 2020. 8. Ho KimAndrea Haselbeck.Background: Climate change affects not only the economy and ecosystem but also health and its social and environmental determinants. Lower- and middle-income countries, which comprise most of the African continent, are more vulnerable to climatic changes and its effects. Various diseases, particularly water and vector-borne, have already started to see an increase in prevalence (i.e cholera) as well as a geographical displacement (i.e malaria). Comprised of a wide variety of climatic zones and already suffering from malnutrition and a variety of infectious diseases, the African continent sees major shifts under a climate change scenario. Particularly, diarrheal diseases, which are a major leading cause of morbidity and mortality, especially in children under five years of age. This study aimed to evaluate the association between temperature and precipitation on all- cause diarrhea for ten different countries in Sub-Saharan Africa.
Method: To analyze the association between the climatic drivers and diarrhea; firstly non-linear exposure-response functions using a natural cubic spline with 2 degrees of freedom were modeled, followed by three different quasi-Poisson generalized linear models for each country and all countries combined; 1- average temperature-diarrhea cases, 2-precipitation-diarrhea cases (controlled for temperature), 3- interaction term of temperature and precipitation -diarrhea cases. Seasonality was controlled for in all models, using a natural cubic spline of time (month of the study period) with 2 df per year. Secondly, group analysis based on geographical location and annual average temperature were conducted for both temperature-diarrhea and precipitation-diarrhea associations. Finally, subgroup analysis was conducted for age and gender.
Results: Three countries showed statistically significant association between temperature and diarrhea cases (Burkina Faso, Ethiopia, Sudan). Burkina Faso showed a protective effect for temperature (12% reduction of diarrhea cases per unit increase of average temperature), whereas Ethiopia and Sudan showed an increased risk (53 and 19 percent increase in diarrhea cases per unit increase of temperature). The precipitation-diarrhea model generally showed positive associations, with statistically significant estimates for Ethiopia and Kenya and for the pooled estimate for all countries (six percent increase in diarrhea for both Ethiopia and Kenya and three percent increase for all countries, per unit increase of precipitation). All age groups showed statistically significant increased (Ethiopia) or reduced risk (Burkina Faso) of diarrhea for average temperature-diarrhea models whereas only the under-five age group showed statistically significant increased risk of diarrhea per unit change of precipitation (Senegal, Kenya, Ethiopia).
Conclusion: The results are consistent with other publications investigating such associations and expand to new study sites previously not investigated. The importance of such results is highlighted when making informed decisions in resource management and allocation, policy, and education programs.๋ฐฐ๊ฒฝ: ๊ธฐํ ๋ณํ๋ ๊ฒฝ์ ์ ์ํ๊ณ๋ฟ๋ง ์๋๋ผ, ๊ฑด๊ฐ ๋ฐ ๊ฑด๊ฐ์ ์ฌํ์ , ํ๊ฒฝ์ ๊ฒฐ์ ์์ธ์๋ ์ํฅ์ ๋ฏธ์น๋ค. ์ํ๋ฆฌ์นด ๋๋ฅ์ ๋๋ถ๋ถ์ ์ฐจ์งํ๋ ์คํ์๊ถ ๊ตญ๊ฐ๋ค์ ๊ธฐํ ๋ณํ์ ๊ทธ ์ํฅ์ ๋ ์ทจ์ฝํ ๊ฒ์ผ๋ก ์๋ ค์ ธ ์๋ค. ๊ฐ์ข
์ง๋ณ, ํนํ ๋ฌผ๊ณผ ๋ฒกํฐ ๋งค๊ฐ ์ง๋ณ์ ์ด๋ฏธ ์ ๋ณ๋ฅ (์ฆ ์ฝ๋ ๋ผ)๋ฟ๋ง ์๋๋ผ ์ง๋ฆฌ์ ๋ณ์(์ฆ ๋ง๋ผ๋ฆฌ์)๋ ์ฆ๊ฐํ๊ธฐ ์์ํ๋ค. ๋ค์ํ ๊ธฐํ ์ง์ญ์ผ๋ก ๊ตฌ์ฑ๋์ด ์๊ณ ์ด๋ฏธ ์์์ค์กฐ์ ๋ค์ํ ์ ์ผ๋ณ์ผ๋ก ๊ณ ํต ๋ฐ๊ณ ์๋ ์ํ๋ฆฌ์นด ๋๋ฅ์ ๊ธฐํ ๋ณํ ์๋๋ฆฌ์ค ํ์์ ์ฃผ์ํ ๋ณํ๋ฅผ ๊ฒช๊ณ ์๋ค. ํนํ, 5์ธ ๋ฏธ๋ง ์๋์๊ฒ ์ง๋ณ๊ณผ ์ฌ๋ง์ ์ฃผ์ ์์ธ์ผ๋ก๋ ์ค์ฌ ์งํ์ด ์ ์๋๊ณ ์๋ค. ๋ณธ ์ฐ๊ตฌ๋ ์ฌํ๋ผ ์ด๋จ ์ํ๋ฆฌ์นด 10๊ฐ๊ตญ์ ์ค์ฌ์ ๋ํ ์จ๋์ ๊ฐ์๋ ์ฌ์ด์ ์ฐ๊ด์ฑ์ ํ๊ฐํ๋ ๊ฒ์ ๋ชฉํ๋ก ํ๋ค.
๋ฐฉ๋ฒ: ๊ธฐํ ์์ธ์ ์ค์ฌ ์ฌ์ด์ ์ฐ๊ด์ฑ ๋ถ์; ๋จผ์ ์์ ๋๊ฐ 2๋์ธ natural cubic spline์ ์ด์ฉํ ๋น์ ํ ๋
ธ์ถ-๋ฐ์ ํจ์๋ฅผ ์ค-ํฌ์์ก ์ผ๋ฐํ ์ ํ ๋ชจํ์ ์ฌ์ฉํ์ฌ ๋ชจ๋ธ๋ง ํ ๋ค์, ๊ฐ ๋๋ผ ๋ฐ ๋ชจ๋ ๊ตญ๊ฐ๋ฅผ ํฉ์น ๊ฒฐ๊ณผ๋ฅผ ์ ์ํ๋ค; 1-ํ๊ท ์จ๋-์ค์ฌ ์ฌ๋ก, 2-๊ฐ์๋๊ณผ ์ค์ฌ ์ฌ๋ก(์จ๋๊ฐ ์ ์ด๋), 3-์จ๋ ๋ฐ ๊ฐ์๋์ ์ค์ฌ ์ฌ๋ก์ ๋ํ ๊ตํธ์์ฉ. ๊ณ์ ์ฑ์ ์ฐ๊ฐ 2df์ natural cubic spline(์ฐ๊ตฌ ๊ธฐ๊ฐ์ ์)์ ์ฌ์ฉํ์ฌ ๋ชจ๋ ๋ชจ๋ธ์์ ๊ณ ๋ ค๋์๋ค. ๋์งธ, ์ง๋ฆฌ์ ์์น์ ์ฐํ๊ท ์จ๋์ ๊ธฐ์ดํ group๋ณ ๋ถ์์ ์จ๋-์ง์ง ๋ฐ ๊ฐ์-์ง์ง ์ฐ๊ด์ฑ ๋ชจ๋์ ๋ํด ์ค์๋์๋ค. ๋ง์ง๋ง์ผ๋ก ์ฐ๋ น๊ณผ ์ฑ๋ณ์ ๋ํ Sub-group ๋ถ์์ ์ค์ํ๋ค.
๊ฒฐ๊ณผ: 3๊ฐ๊ตญ์ ๊ธฐ์จ๊ณผ ์ค์ฌ ํ์ ์ฌ์ด์ ํต๊ณ์ ์ผ๋ก ์ ์๋ฏธํ ์ฐ๊ด์ฑ์ ๋ณด์๋ค(๋ถ๋ฅดํค๋ํ์, ์ํฐ์คํผ์, ์๋จ). ๋ถ๋ฅดํค๋ํ์๋ ๊ธฐ์จ์ ๋ํ protectiveํ ๊ด๊ณ(์จ๋ ์์น๋น 12%์ ์ค์ฌํ์ ๊ฐ์)๋ฅผ ๋ณด์ธ ๋ฐ๋ฉด ์ํฐ์คํผ์์ ์๋จ์ ์ํ์ฑ์ด ์ฆ๊ฐ(์จ๋ ์์น๋น ์ค์ฌํ์ ๊ฐ 53%, 19% ์ฆ๊ฐ)ํ๋ค. ๊ฐ์-์ง์ง ๋ชจํ์ ์ผ๋ฐ์ ์ผ๋ก ์์ ์ฐ๊ด์ฑ์ ๋ณด์ฌ์ฃผ์๋๋ฐ, ํต๊ณ์ ์ผ๋ก ์ ์ํ ์ถ์ ์น๋ ์ํฐ์คํผ์์ ์ผ๋์ ๋ชจ๋ ๊ตญ๊ฐ์ ๋ํ ํฉ๋ ์ถ์ ์น์๋ค(๊ฐ์๋ ๋จ์ ์ฆ๊ฐ ๋น ์ดํฐ์คํผ์์ ์ผ๋์ ๊ฒฝ์ฐ ์ค์ฌ๊ฐ 6% ์ฆ๊ฐ, ๋ชจ๋ ๊ตญ๊ฐ์ ๊ฒฝ์ฐ 3% ์ฆ๊ฐ).
๊ฒฐ๋ก : ๋ณธ ์ฐ๊ตฌ์ ๊ฒฐ๊ณผ๋ ์จ๋- ๋ฐ ๊ฐ์๋๊ณผ ์ค์ฌ ์ฌ๋ก์ ์ฐ๊ด์ฑ์ ์กฐ์ฌํ๋ ๋ค๋ฅธ ๊ธฐ์กด ์ฐ๊ตฌ๋ค๊ณผ ์ผ์นํ๋ฉฐ, ์ด์ ์ ์กฐ์ฌ๋์ง ์์๋ ์๋ก์ด ์ฐ๊ตฌ ์ง์ญ์ ํฌํจํ์ฌ ํ์ฅ๋์ด ์ํ๋์๋ค. ๋ณธ ์ฐ๊ตฌ ๊ฒฐ๊ณผ๋ ์์ ๊ด๋ฆฌ์ ํ ๋น, ์ ์ฑ
๋ฐ ๊ต์ก ํ๋ก๊ทธ๋จ์์ ์ ๋ณด์ ์
๊ฐํ ์์ฌ๊ฒฐ์ ์ ๋ด๋ฆด ๋ ์ค์ํ๊ฒ ์ฌ์ฉ๋ ์ ์๋ค.1. Introduction 11
2. Methods 13
2.1 Datasets & Descriptive statistics
2.2 Statistical analysis
3. Results 19
3.1 Descriptive results
3.2 Statistical analysis results
4. Discussion 30
Limitations
Strengths
Conclusion
5. Appendix 39
6. References 49
Index of Figures
Figure 1.Map of Africa, highlighting study sites and the yearly diarrhea cases per each study year 22
Figure 2. Map of the Africa, highlighting the study sites and 7-year averages of climate drivers 23
Figure 3. Non-linear exposure-response plots of temperature and relative risk of diarrhea 25
Figure 4. Non-linear exposure-response plots of precipitation and relative risk of diarrhea 27
Fig A- 1. Time -Series plots of average temperature, precipitation, and diarrhea cases per country 41
Fig A-2. Non-linear exposure-response plots of temperature and relative risk of diarrhea for under 5 years old age group 46
Fig A- 3.Non-linear exposure-response plots of temperature and relative risk of diarrhea for over 5 years old age group 46
Fig A- 4. Non-linear exposure-response plots of temperature and relative risk of diarrhea for males 47
Fig A- 5.Non-linear exposure-response plots of temperature and relative risk of diarrhea for females 47
Fig A- 6. Non-linear exposure-response plots of precipitation and relative risk of diarrhea for under 5 years old 48
Fig A- 7. Non-linear exposure-response plots of precipitation and relative risk of diarrhea for over 5 years age group 48
Fig A- 8. Non-linear exposure-response plots of precipitation and relative risk of diarrhea for males 49
Fig A- 9. Non-linear exposure-response plots of precipitation and relative risk of diarrhea for females 49
Index of Tables
Table 1. List of TSAP study sites, study period and number of diarrhea cases 16
Table 2.NOAA Climate indicator coverage for 2009-2015. 16
Table 3. Diarrhea cases per country by age and gender 21
Table 4.Relative Risk of diarrhea per unit increase of temperature 25
Table 5.Relative risk of diarrhea per unit increase of precipitation 27
Table 6. Results of risk ratio for diarrhea by interactions between precipitation and temperature 28
Table A- 1. Distribution of diarrhea cases for each country by study year 40
Table A- 2. Climate characteristics & seasons by country 42
Table A- 3.Seasonal temperature characteristic by country 43
Table A- 4. Risk ratio of diarrhea for average temperature for grouped countries 43
Table A- 5. Risk ratio of diarrhea for precipitation for geographically grouped countries 44
Table A- 6. Risk ratio of diarrhea for interaction of temperature and precipitation 44
Table A- 7. Risk ratio of diarrhea for average temperature per age group 44
Table A- 8.Risk ratio of diarrhea for precipitation per age group 44
Table A- 9.Risk ratio of diarrhea for temperature per gender 45
Table A- 10. Risk ratio of diarrhea for precipitation per gender 45Maste
CS MQP - TCP Congestion Control over a Satellite Network
Dynamic Adaptive Streaming over HTTP (DASH) is a popular, modern method for streaming media. Adaptive bitrate (ABR) functionality allows DASH to adjust to changing network conditions during the course of the stream. However, little work has assessed DASH's performance over geostationary satellite networks, where high latencies cause many network protocols to perform poorly. This paper presents results from experiments that evaluate DASH over a commercial geostationary satellite connection, comparing performance when adjusting two different configuration settings of the stream: The length of video segments, and the ABR algorithm used to make decisions. Results show that: 1) longer segment lengths are more stable but fail to adjust bitrate, staying at a low video quality; and 2) the buffer-based BOLA ABR algorithm has fewer stalls and better video quality than either a throughput-based approach or a hybrid approach
CS MQP - Analyzing DASH Video Streaming over Geostationary Satellite Networks
Dynamic Adaptive Streaming over HTTP (DASH) is a popular, modern method for streaming media. Adaptive bitrate (ABR) functionality allows DASH to adjust to changing network conditions during the course of the stream. However, little work has assessed DASH's performance over geostationary satellite networks, where high latencies cause many network protocols to perform poorly. This paper presents results from experiments that evaluate DASH over a commercial geostationary satellite connection, comparing performance when adjusting two different configuration settings of the stream: The length of video segments, and the ABR algorithm used to make decisions. Results show that: 1) longer segment lengths are more stable but fail to adjust bitrate, staying at a low video quality; and 2) the buffer-based BOLA ABR algorithm has fewer stalls and better video quality than either a throughput-based approach or a hybrid approach
Improving Outdoors Literacy For Children At Turn Back Time
Studies show that exposure to nature and play-based learning are critical to early childhood development. Turn Back Time Inc. (TBT) provides the opportunity of outdoors learning to children through various daily activities and experiential play in nature. While TBT possesses a rudimentary trail for outdoors literacy, the lack of long-term structural units stunts the efficacy of their outdoors literature process. The purpose of this study was to research, construct and analyze nature-based literacy stations to improve TBTโs outdoor learning facilities and to enhance the literature experience of TBT students
Serology as a Tool to Assess Infectious Disease Landscapes and Guide Public Health Policy.
Understanding the local burden and epidemiology of infectious diseases is crucial to guide public health policy and prioritize interventions. Typically, infectious disease surveillance relies on capturing clinical cases within a healthcare system, classifying cases by etiology and enumerating cases over a period of time. Disease burden is often then extrapolated to the general population. Serology (i.e., examining serum for the presence of pathogen-specific antibodies) has long been used to inform about individuals past exposure and immunity to specific pathogens. However, it has been underutilized as a tool to evaluate the infectious disease burden landscape at the population level and guide public health decisions. In this review, we outline how serology provides a powerful tool to complement case-based surveillance for determining disease burden and epidemiology of infectious diseases, highlighting its benefits and limitations. We describe the current serology-based technologies and illustrate their use with examples from both the pre- and post- COVID-19-pandemic context. In particular, we review the challenges to and opportunities in implementing serological surveillance in low- and middle-income countries (LMICs), which bear the brunt of the global infectious disease burden. Finally, we discuss the relevance of serology data for public health decision-making and describe scenarios in which this data could be used, either independently or in conjunction with case-based surveillance. We conclude that public health systems would greatly benefit from the inclusion of serology to supplement and strengthen existing case-based infectious disease surveillance strategies
Projections of excess mortality related to diurnal temperature range under climate change scenarios: a multi-country modelling study
Summary
Background
Various retrospective studies have reported on the increase of mortality risk due to higher diurnal temperature range (DTR). This study projects the effect of DTR on future mortality across 445 communities in 20 countries and regions.
Methods
DTR-related mortality risk was estimated on the basis of the historical daily time-series of mortality and weather factors from Jan 1, 1985, to Dec 31, 2015, with data for 445 communities across 20 countries and regions, from the Multi-Country Multi-City Collaborative Research Network. We obtained daily projected temperature series associated with four climate change scenarios, using the four representative concentration pathways (RCPs) described by the Intergovernmental Panel on Climate Change, from the lowest to the highest emission scenarios (RCP 2.6, RCP 4.5, RCP 6.0, and RCP 8.5). Excess deaths attributable to the DTR during the current (1985โ2015) and future (2020โ99) periods were projected using daily DTR series under the four scenarios. Future excess deaths were calculated on the basis of assumptions that warmer long-term average temperatures affect or do not affect the DTR-related mortality risk.
Findings
The time-series analyses results showed that DTR was associated with excess mortality. Under the unmitigated climate change scenario (RCP 8.5), the future average DTR is projected to increase in most countries and regions (by โ0ยท4 to 1ยท6ยฐC), particularly in the USA, south-central Europe, Mexico, and South Africa. The excess deaths currently attributable to DTR were estimated to be 0ยท2โ7ยท4%. Furthermore, the DTR-related mortality risk increased as the long-term average temperature increased; in the linear mixed model with the assumption of an interactive effect with long-term average temperature, we estimated 0ยท05% additional DTR mortality risk per 1ยฐC increase in average temperature. Based on the interaction with long-term average temperature, the DTR-related excess deaths are projected to increase in all countries or regions by 1ยท4โ10ยท3% in 2090โ99.
Interpretation
This study suggests that globally, DTR-related excess mortality might increase under climate change, and this increasing pattern is likely to vary between countries and regions. Considering climatic changes, our findings could contribute to public health interventions aimed at reducing the impact of DTR on human health.Peer reviewe
Projections of Excessive Mortality Related to Diurnal Temperature Range Under Climate Change Scenarios: A Multi-Country Study
Projections of excess mortality related to diurnal temperature range under climate change scenarios:a multi-country modelling study
Abstract
Background: Various retrospective studies have reported on the increase of mortality risk due to higher diurnal temperature range (DTR). This study projects the effect of DTR on future mortality across 445 communities in 20 countries and regions.
Methods: DTR-related mortality risk was estimated on the basis of the historical daily time-series of mortality and weather factors from Jan 1, 1985, to Dec 31, 2015, with data for 445 communities across 20 countries and regions, from the Multi-Country Multi-City Collaborative Research Network. We obtained daily projected temperature series associated with four climate change scenarios, using the four representative concentration pathways (RCPs) described by the Intergovernmental Panel on Climate Change, from the lowest to the highest emission scenarios (RCP 2.6, RCP 4.5, RCP 6.0, and RCP 8.5). Excess deaths attributable to the DTR during the current (1985โ2015) and future (2020โ99) periods were projected using daily DTR series under the four scenarios. Future excess deaths were calculated on the basis of assumptions that warmer long-term average temperatures affect or do not affect the DTR-related mortality risk.
Findings: The time-series analyses results showed that DTR was associated with excess mortality. Under the unmitigated climate change scenario (RCP 8.5), the future average DTR is projected to increase in most countries and regions (by โ0ยท4 to 1ยท6ยฐC), particularly in the USA, south-central Europe, Mexico, and South Africa. The excess deaths currently attributable to DTR were estimated to be 0ยท2โ7ยท4%. Furthermore, the DTR-related mortality risk increased as the long-term average temperature increased; in the linear mixed model with the assumption of an interactive effect with long-term average temperature, we estimated 0ยท05% additional DTR mortality risk per 1ยฐC increase in average temperature. Based on the interaction with long-term average temperature, the DTR-related excess deaths are projected to increase in all countries or regions by 1ยท4โ10ยท3% in 2090โ99.
Interpretation: This study suggests that globally, DTR-related excess mortality might increase under climate change, and this increasing pattern is likely to vary between countries and regions. Considering climatic changes, our findings could contribute to public health interventions aimed at reducing the impact of DTR on human health