symbol_cluster
listlengths 6
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|---|---|---|---|---|---|---|---|---|---|---|---|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22,
23,
24,
25,
26,
27,
28,
29,
30,
31,
32
] |
[
8144
] |
[
95042
] |
Neamatullah describes a Perl-based de-identification software package [9] based on lexical look-up tables, regular expressions, and simple rules to identify PHI in medical text documents.
| 9
|
[
8144,
95042
] |
PMC2923159
|
PMC2526997
|
Automatic de-identification of textual documents in the electronic health record: a review of recent research
|
Automated de-identification of free-text medical records
|
competing interests
|
competing interests
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22,
23,
24,
25,
26,
27,
28,
29,
30,
31,
32
] |
[
8144
] |
[
84803
] |
HMS Scrubber was developed by Beckwith [14] and is an open source, HIPAA compliant, de-identification tool tailored for pathology reports.
| 14
|
[
8144,
84803
] |
PMC2923159
|
PMC1421388
|
Automatic de-identification of textual documents in the electronic health record: a review of recent research
|
Development and evaluation of an open source software tool for deidentification of pathology reports
|
competing interests
|
competing interests
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10
] |
[
9198
] |
[
99328
] |
Although modelling is beginning to be used for this purpose [2], it is often inaccessible to the majority of those planning malaria elimination efforts.
| 2
|
[
9198,
99328
] |
PMC3160427
|
PMC2660356
|
Modelling malaria elimination on the internet
|
The last man standing is the most resistant: eliminating artemisinin-resistant malaria in Cambodia
|
competing interests
|
competing interests
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10
] |
[
9169,
9170,
9171,
9172,
9173,
9174,
9175,
9176,
9177
] |
[
110549,
110550,
110551
] |
Mathematical modelling has great potential as a tool to help guide efforts towards malaria elimination [1].
| 1
|
[
9169,
110549
] |
PMC3160427
|
PMC3004029
|
Modelling malaria elimination on the internet
|
The role of mathematical modelling in guiding the science and economics of malaria elimination
|
introduction
|
abstract
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10
] |
[
9169,
9170,
9171,
9172,
9173,
9174,
9175,
9176,
9177
] |
[
110549,
110550,
110551
] |
It could potentially be used for preliminary evaluation of different strategies for malaria elimination in different epidemiological contexts much more rapidly and at lower cost than is possible through trial and error in the field [1].
| 1
|
[
9169,
110549
] |
PMC3160427
|
PMC3004029
|
Modelling malaria elimination on the internet
|
The role of mathematical modelling in guiding the science and economics of malaria elimination
|
introduction
|
abstract
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22
] |
[
46294,
46295,
46296,
46297,
46298,
46299
] |
[
211703,
211704,
211705,
211706
] |
The child is observed performing a set of tasks associated with specific interrelated domains and evaluated based on direct structured observations of the expected behavior, caregiver reports, or unstructured observation from evaluators [2].
| 2
|
[
46295,
211703
] |
PMC6695133
|
PMC4413834
|
Validation of the Malawi Developmental Assessment Tool for children in the Dominican Republic: Preliminary results
|
Child development assessment tools in low-income and middle-income countries: how can we use them more appropriately?
|
introduction
|
types of assessment tools—screening versus formal assessment?
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22
] |
[
46294,
46295,
46296,
46297,
46298,
46299
] |
[
211703,
211704,
211705,
211706
] |
As the assessment progresses, the child engages in activities of increasing difficulty [2].
| 2
|
[
46295,
211703
] |
PMC6695133
|
PMC4413834
|
Validation of the Malawi Developmental Assessment Tool for children in the Dominican Republic: Preliminary results
|
Child development assessment tools in low-income and middle-income countries: how can we use them more appropriately?
|
introduction
|
types of assessment tools—screening versus formal assessment?
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22
] |
[
46294,
46295,
46296,
46297,
46298,
46299
] |
[
211703,
211704,
211705,
211706
] |
However, although developmental screening tools have the potential to infer about general development milestones, and probably detect children with significant impairments that require further testing, the use of screening tools may not be able to identify subtle developmental delays [2].
| 2
|
[
46295,
211703
] |
PMC6695133
|
PMC4413834
|
Validation of the Malawi Developmental Assessment Tool for children in the Dominican Republic: Preliminary results
|
Child development assessment tools in low-income and middle-income countries: how can we use them more appropriately?
|
introduction
|
types of assessment tools—screening versus formal assessment?
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22,
23,
24,
25,
26,
27
] |
[
46653,
46654,
46655
] |
[
128394,
128395
] |
Risk of bias assessment was done using Cochrane methodology [20] by evaluating for random sequence generation, allocation concealment, incomplete or selective outcome data reporting, blinding of participants and personnel, blinding of outcome assessment, attrition, and other sources of bias.
| 20
|
[
46654,
128394
] |
PMC6731021
|
PMC3196245
|
Comparison of oral versus parenteral methotrexate in the treatment of rheumatoid arthritis: A meta-analysis
|
The Cochrane Collaboration’s tool for assessing risk of bias in randomised trials
|
adverse events
|
data
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10
] |
[
51021,
51022,
51023,
51024
] |
[
362617,
362618,
362619,
362620
] |
However, implementation of isolation and quarantine procedures helped to prevent the spread of COVID-19 in more than 2000 passengers and lowered the R0 to 1.78 [6].
| 6
|
[
51021,
362617
] |
PMC7156123
|
PMC7107563
|
Global epidemiology of coronavirus disease 2019 (COVID-19): disease incidence, daily cumulative index, mortality, and their association with country healthcare resources and economic status
|
COVID-19 outbreak on the Diamond Princess cruise ship: estimating the epidemic potential and effectiveness of public health countermeasures
|
international conveyance (diamond princess)
|
introduction
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10
] |
[
51041,
51042,
51043
] |
[
306171,
306172,
306173,
306174
] |
The HAQI uses 32 scaled cause values, providing an overall score of 0–100 of personal healthcare access and quality by location over time [10].
| 10
|
[
51042,
306171
] |
PMC7156123
|
PMC5986687
|
Global epidemiology of coronavirus disease 2019 (COVID-19): disease incidence, daily cumulative index, mortality, and their association with country healthcare resources and economic status
|
Measuring performance on the Healthcare Access and Quality Index for 195 countries and territories and selected subnational locations: a systematic analysis from the Global Burden of Disease Study 2016
|
association between mortality and disease incidence
|
correlates of haq index performance
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12
] |
[
59447,
59448
] |
[
176615,
176616,
176617,
176618
] |
Cut throat injuries poses a great surgical challenge because multiple vital structure are vulnerable to injuries in the small, confined unprotected area [3].
| 3
|
[
59447,
176616
] |
PMC7584311
|
PMC3893495
|
An Epidemiological Study of Cut Throat Injury During COVID-19 Pandemic in a Tertiary Care Centre
|
Cut throat injuries at a university teaching hospital in northwestern Tanzania: a review of 98 cases
|
introduction
|
introduction
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22,
23,
24,
25,
26,
27,
28,
29,
30,
31,
32,
33
] |
[
64372,
64373,
64374
] |
[
63827,
63828,
63829,
63830,
63831
] |
Some of the present findings are in line with a recently published narrative review of studies examining vaccine intentions by Lin et al [23].
| 23
|
[
64374,
63829
] |
PMC7867398
|
PMC7823859
|
International estimates of intended uptake and refusal of COVID-19 vaccines: A rapid systematic review and meta-analysis of large nationally representative samples
|
Confidence and Receptivity for COVID-19 Vaccines: A Rapid Systematic Review
|
abstract
|
abstract
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22,
23,
24,
25,
26,
27,
28,
29,
30,
31,
32,
33
] |
[
64372,
64373,
64374
] |
[
63827,
63828,
63829,
63830,
63831
] |
[23] included a number of small non-representative samples and results from news reports in their review.
| 23
|
[
64374,
63829
] |
PMC7867398
|
PMC7823859
|
International estimates of intended uptake and refusal of COVID-19 vaccines: A rapid systematic review and meta-analysis of large nationally representative samples
|
Confidence and Receptivity for COVID-19 Vaccines: A Rapid Systematic Review
|
abstract
|
abstract
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22,
23,
24,
25,
26,
27,
28,
29,
30,
31,
32,
33
] |
[
64897,
64898
] |
[
393383
] |
A systematic review and meta-analysis of COVID-19 clinical outcomes found that males constituted a significantly higher proportion of those who had adverse clinical outcomes and died from COVID-19 [31].
| 31
|
[
64897,
393383
] |
PMC7885691
|
PMC7331754
|
Perspectives on the receipt of a COVID-19 vaccine: A survey of employees in two large hospitals in Philadelphia
|
Systematic Review and Meta-Analysis of Sex-Specific COVID-19 Clinical Outcomes
|
competing interests
|
competing interests
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22,
23,
24,
25,
26,
27,
28,
29,
30,
31,
32,
33,
34,
35,
36,
37,
38
] |
[
67481,
67482
] |
[
366632,
366633,
366634
] |
In [27] the authors considered a fractional model in terms of the fractal-fractional Atangana–Baleanu derivative for describing the spread of COVID-19 taking into account quarantine and isolation.
| 27
|
[
67481,
366632
] |
PMC8057057
|
PMC7148705
|
A new fractional mathematical modelling of COVID-19 with the availability of vaccine
|
Modeling the dynamics of novel coronavirus (2019-nCov) with fractional derivative
|
the disease-free equilibrium (dfe)
|
results/conclusion
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22,
23,
24,
25,
26,
27,
28,
29,
30,
31,
32,
33,
34,
35,
36,
37,
38
] |
[
67506
] |
[
407261
] |
These actions include among others social distancing, compulsory use of nose mask and temporal lockdown of commercial establishments [9].
| 9
|
[
67506,
407261
] |
PMC8057057
|
PMC7448803
|
A new fractional mathematical modelling of COVID-19 with the availability of vaccine
|
The Covid-19 outbreak in Spain. A simple dynamics model, some lessons, and a theoretical framework for control response
|
competing interests
|
competing interests
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22,
23,
24,
25,
26,
27,
28,
29,
30,
31,
32,
33,
34,
35,
36,
37,
38,
39,
40,
41,
42,
43,
44,
45,
46,
47,
48,
49,
50,
51,
52,
53,
54
] |
[
70473
] |
[
395207
] |
We observe a change point in the general population behavior after the announcement, which was delayed to the IV epidemiological period because of the disease timeline (latency, incubation, recovery time) and significant delays in testing [24].
| 24
|
[
70473,
395207
] |
PMC8196305
|
PMC7341964
|
On the heterogeneous spread of COVID-19 in Chile
|
Statistically-based methodology for revealing real contagion trends and correcting delay-induced errors in the assessment of COVID-19 pandemic
|
competing interests
|
competing interests
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22,
23,
24,
25,
26,
27,
28,
29,
30,
31,
32,
33,
34,
35,
36,
37,
38,
39,
40,
41,
42,
43,
44,
45,
46,
47,
48,
49,
50,
51,
52,
53,
54
] |
[
70473
] |
[
431578
] |
[45], Medina-Ortiz et al.
| 45
|
[
70473,
431578
] |
PMC8196305
|
PMC7783316
|
On the heterogeneous spread of COVID-19 in Chile
|
Real-Time Estimation of Rt for Supporting Public-Health Policies Against COVID-19
|
competing interests
|
competing interests
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22,
23,
24,
25,
26,
27,
28,
29,
30,
31,
32,
33,
34,
35,
36,
37,
38,
39,
40,
41,
42,
43,
44,
45,
46,
47,
48,
49,
50,
51,
52,
53,
54
] |
[
70473
] |
[
436237,
436238
] |
Viral spread depends not only on its biological properties but also on the behavior and susceptibility of the population where it propagates [20].
| 20
|
[
70473,
436237
] |
PMC8196305
|
PMC7836337
|
On the heterogeneous spread of COVID-19 in Chile
|
Impacts of geographic factors and population density on the COVID-19 spreading under the lockdown policies of China
|
competing interests
|
competing interests
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22,
23
] |
[
74087,
74088,
74089
] |
[
218030,
218031,
218032
] |
From the previous discussion, the main goal of the present study was to describe a hybrid approach [10], i.e., a methodology that holistically mixes mathematical modeling and experimental design, which is required, as shown in the literature, for better understanding the studied system by fitting parameters of a given model with a specific scenario and for obtaining models with predictive capability.
| 10
|
[
74087,
218032
] |
PMC8480140
|
PMC4509478
|
Forecasting COVID-19 Chile’ second outbreak by a generalized SIR model with constant time delays and a fitted positivity rate
|
Proposal of a hybrid approach for tumor progression and tumor-induced angiogenesis
|
scenarios for the fittings and forecastings
|
basic principles of mathematical modelling of tumor growth
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22,
23,
24,
25,
26,
27,
28,
29,
30,
31,
32,
33,
34,
35,
36,
37,
38,
39,
40,
41,
42,
43,
44,
45,
46,
47,
48,
49,
50,
51,
52,
53,
54,
55,
56,
57,
58,
59,
60,
61
] |
[
75263
] |
[
175244
] |
However, it does not leverage the power of specialized medical image processing libraries, such as SimpleITK [14], to process volumetric images.
| 14
|
[
75263,
175244
] |
PMC8542803
|
PMC3874546
|
TorchIO: A Python library for efficient loading, preprocessing, augmentation and patch-based sampling of medical images in deep learning
|
The Design of SimpleITK
|
competing interests
|
competing interests
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20
] |
[
75896
] |
[
410972
] |
[19] measured the effectiveness of aerosol sanitizer mixed air from air conditioner used to disinfect the room having COVID-19 virus.
| 19
|
[
75896,
410972
] |
PMC8577579
|
PMC7498234
|
Computational fluid dynamics-based disease transmission modeling of SARS-CoV-2 Intensive Care Unit
|
A novel CFD analysis to minimize the spread of COVID-19 virus in hospital isolation room
|
competing interests
|
competing interests
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20
] |
[
75896
] |
[
456954
] |
[20] analyzed the effect of installing transparent barriers in front of classroom seats in order to prevent the effect of coughing or sneezing of a COVID-19 infected person standing in the front area of the classroom.
| 20
|
[
75896,
456954
] |
PMC8577579
|
PMC8270738
|
Computational fluid dynamics-based disease transmission modeling of SARS-CoV-2 Intensive Care Unit
|
COVID-19 spread in a classroom equipped with partition – A CFD approach
|
competing interests
|
competing interests
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20
] |
[
75881,
75882,
75883,
75884,
75885,
75886
] |
[
419878,
419879,
419880,
419881,
419882
] |
The consideration of shape, size as well as evaporation kinetics of these particles are necessary as these properties of particles have a significant impact on the transport of aerosol as well as droplets in the system [2].
| 2
|
[
75881,
419878
] |
PMC8577579
|
PMC7583363
|
Computational fluid dynamics-based disease transmission modeling of SARS-CoV-2 Intensive Care Unit
|
Numerical investigation of aerosol transport in a classroom with relevance to COVID-19
|
governing equations
|
airflow and particle dynamics
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22,
23,
24,
25,
26,
27
] |
[
173706
] |
[
125011
] |
It has been reported that low IPTp coverage levels could be attributed to unclear IPTp guidelines that lead to lost effectiveness of the IPTp strategy [12].
| 12
|
[
173706,
125011
] |
PMC3850646
|
PMC3126755
|
Why are IPTp coverage targets so elusive in sub-Saharan Africa? A systematic review of health system barriers
|
The combined effect of determinants on coverage of intermittent preventive treatment of malaria during pregnancy in the Kilombero Valley, Tanzania
|
competing interests
|
competing interests
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22,
23,
24,
25,
26,
27
] |
[
173706
] |
[
94232
] |
Evaluation of an IPTp roll-out programme in an African country revealed existence of conflicting health care worker guidelines for IPTp [13].
| 13
|
[
173706,
94232
] |
PMC3850646
|
PMC2500039
|
Why are IPTp coverage targets so elusive in sub-Saharan Africa? A systematic review of health system barriers
|
Prospects, achievements, challenges and opportunities for scaling-up malaria chemoprevention in pregnancy in Tanzania: the perspective of national level officers
|
competing interests
|
competing interests
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22,
23,
24,
25,
26,
27
] |
[
173706
] |
[
136039
] |
In Tanzania, in-depth interviews among national level malaria control officers revealed a need to address leadership constraints to IPTp policy implementation through decentralization [14].
| 14
|
[
173706,
136039
] |
PMC3850646
|
PMC3298537
|
Why are IPTp coverage targets so elusive in sub-Saharan Africa? A systematic review of health system barriers
|
Supply-related drivers of staff motivation for providing intermittent preventive treatment of malaria during pregnancy in Tanzania: evidence from two rural districts
|
competing interests
|
competing interests
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22,
23,
24,
25,
26,
27,
28,
29,
30,
31,
32,
33,
34,
35,
36,
37,
38,
39,
40,
41,
42,
43,
44,
45,
46,
47,
48,
49,
50,
51
] |
[
179877,
179878,
179879
] |
[
169307,
169308,
169309,
169310,
169311,
169312
] |
Directly relevant to the current investigation, it has recently been shown that endorsement of a variety of unrelated conspiracy theories is associated with negative attitudes toward vaccination [26].
| 26
|
[
179877,
169311
] |
PMC3930676
|
PMC3788812
|
The Effects of Anti-Vaccine Conspiracy Theories on Vaccination Intentions
|
The Role of Conspiracist Ideation and Worldviews in Predicting Rejection of Science
|
abstract
|
conspiracist ideation vs. scientific cognition
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22,
23,
24,
25,
26,
27,
28
] |
[
204194,
204195,
204196
] |
[
155627,
155628,
155629,
155630
] |
Specifically, Chaudoir et al.’s instrument review focused only on predictive validity [5].
| 5
|
[
204195,
155629
] |
PMC4308900
|
PMC3598720
|
The Society for Implementation Research Collaboration Instrument Review Project: A methodology to promote rigorous evaluation
|
Measuring factors affecting implementation of health innovations: a systematic review of structural, organizational, provider, patient, and innovation level measures
|
abstract
|
criterion validity
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22,
23,
24,
25,
26,
27,
28
] |
[
204194,
204195,
204196
] |
[
155627,
155628,
155629,
155630
] |
[5] employed a systematic review of key DIS domains (i.e., structural, organizational, provider, patient, and innovation, as opposed to constructs: e.g., intervention adaptability, external policy, and incentives), they identified only 62 instruments which is substantially fewer than the 420+ instruments revealed by the SIRC methodology.
| 5
|
[
204195,
155629
] |
PMC4308900
|
PMC3598720
|
The Society for Implementation Research Collaboration Instrument Review Project: A methodology to promote rigorous evaluation
|
Measuring factors affecting implementation of health innovations: a systematic review of structural, organizational, provider, patient, and innovation level measures
|
abstract
|
criterion validity
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22,
23,
24,
25,
26,
27,
28
] |
[
204194,
204195,
204196
] |
[
185368,
185369,
185370,
185371,
185372
] |
Our preliminary results also signal a need for new instrumentation targeting non-provider stakeholders such as leaders and external change agents (e.g., implementation practitioners or intermediaries), particularly in light of research identifying the role they play in implementation success (e.g., [25]).
| 25
|
[
204195,
185368
] |
PMC4308900
|
PMC4022333
|
The Society for Implementation Research Collaboration Instrument Review Project: A methodology to promote rigorous evaluation
|
The implementation leadership scale (ILS): development of a brief measure of unit level implementation leadership
|
abstract
|
abstract
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22,
23,
24,
25,
26,
27,
28,
29,
30,
31,
32,
33,
34,
35,
36,
37,
38,
39,
40,
41,
42,
43,
44,
45,
46,
47,
48,
49,
50,
51,
52,
53,
54,
55,
56,
57,
58,
59,
60,
61,
62,
63,
64,
65,
66,
67,
68,
69,
70
] |
[
217726
] |
[
92127,
92128,
92129
] |
Age-based social contact pattern surveys, which may inform short-cycle transmission [62].
| 62
|
[
217726,
92129
] |
PMC4504000
|
PMC2270306
|
A review of typhoid fever transmission dynamic models and economic evaluations of vaccination
|
Social Contacts and Mixing Patterns Relevant to the Spread of Infectious Diseases
|
discussion
|
simulated initial phase of an epidemic
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22,
23
] |
[
232799,
232800,
232801,
232802,
232803,
232804
] |
[
113354,
113355,
113356,
113357,
113358
] |
Of the approximate 100 countries with endemic malaria, 34 were defined in 2010 as malaria-eliminating (see Table 1), defined here as a country that has a national or subnational evidence-based elimination goal and/or is actively pursuing elimination (zero malaria transmission) within its borders [1].
| 1
|
[
232802,
113357
] |
PMC4766696
|
PMC3044848
|
Global fund financing to the 34 malaria-eliminating countries under the new funding model 2014–2017: an analysis of national allocations and regional grants
|
Shrinking the malaria map: progress and prospects
|
results/conclusion
|
risks of elimination
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22,
23
] |
[
232799,
232800,
232801,
232802,
232803,
232804
] |
[
113354,
113355,
113356,
113357,
113358
] |
As of 2010, 34 countries have been identified as malaria-eliminating [1].
| 1
|
[
232802,
113357
] |
PMC4766696
|
PMC3044848
|
Global fund financing to the 34 malaria-eliminating countries under the new funding model 2014–2017: an analysis of national allocations and regional grants
|
Shrinking the malaria map: progress and prospects
|
results/conclusion
|
risks of elimination
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22,
23
] |
[
232805
] |
[
145270,
145271,
145272
] |
Historical evidence suggests that if malaria funds are interrupted, programmes are weakened, or interventions are disrupted before malaria has been eliminated, there is a danger of malaria resurgence [22].
| 22
|
[
232805,
145271
] |
PMC4766696
|
PMC3458906
|
Global fund financing to the 34 malaria-eliminating countries under the new funding model 2014–2017: an analysis of national allocations and regional grants
|
Malaria resurgence: a systematic review and assessment of its causes
|
data
|
reported causes of resurgence
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22,
23,
24,
25,
26,
27,
28,
29,
30,
31,
32,
33,
34,
35,
36,
37,
38,
39,
40,
41,
42,
43,
44,
45,
46,
47,
48,
49,
50,
51
] |
[
237531,
237532,
237533
] |
[
145676,
145677
] |
For instance, IpaB was shown in vitro to oligomerize and insert into the plasma membrane of target cells, forming cation selective ion channels involved in vacuolar rupture [24].
| 24
|
[
237531,
145676
] |
PMC4868309
|
PMC3461361
|
Macropinosomes are Key Players in Early Shigella Invasion and Vacuolar Escape in Epithelial Cells
|
Spontaneous formation of IpaB ion channels in host cell membranes reveals how Shigella induces pyroptosis in macrophages
|
newly formed macropinosomes are the major compartment at the s. flexneri invasion site
|
statistical analysis
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10
] |
[
246933,
246934,
246935,
246936
] |
[
96844,
96845,
96846,
96847
] |
The ZiBRA team, with the help of LACEN personnel, tested 1349 samples for ZIKV RNA across Rio Grande do Norte, Paraíba, Recife, Maceió, and Bahia states, using previously described protocols [10] and the Rotor-Gene Q (Qiagen).
| 10
|
[
246935,
96844
] |
PMC5041528
|
PMC2600394
|
Mobile real-time surveillance of Zika virus in Brazil
|
Genetic and Serologic Properties of Zika Virus Associated with an Epidemic, Yap State, Micronesia, 2007
|
introduction
|
discussion
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17
] |
[
262331,
262332,
262333,
262334
] |
[
263557
] |
Furthermore, as observed in a previous study, [13] the WHO matrix of determinants was demonstrated to be robust, as only a few factors identified in the survey fell outside of the scope of the matrix.
| 13
|
[
262334,
263557
] |
PMC5332020
|
PMC5355208
|
Assessments of global drivers of vaccine hesitancy in 2014—Looking beyond safety concerns
|
Mapping vaccine hesitancy—Country-specific characteristics of a global phenomenon
|
discussion
|
determinants of vaccine hesitancy using the working group matrix
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22
] |
[
310304,
310305
] |
[
208010,
208011,
208012
] |
Given the heterogeneity in DREAMS’ delivery, we will monitor how, when, by whom, and to whom, components of the DREAMS package are delivered, in the process evaluation activities described below [10].
| 10
|
[
310304,
208011
] |
PMC6060450
|
PMC4366184
|
Evaluating the impact of the DREAMS partnership to reduce HIV incidence among adolescent girls and young women in four settings: a study protocol
|
Process evaluation of complex interventions: Medical Research Council guidance
|
data
|
learning from previous process evaluations
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20
] |
[
341447,
341448,
341449,
341450,
341451
] |
[
274467,
274468,
274469
] |
NFL concentrations also correlate with measures of cognition and brain atrophy in Huntington’s disease [20], indicating that it might be a promising marker for upcoming treatment regimes in diseases beside SMA.
| 20
|
[
341449,
274467
] |
PMC6687695
|
PMC5507767
|
NFL is a marker of treatment response in children with SMA treated with nusinersen
|
Neurofilament light protein in blood as a potential biomarker of neurodegeneration in Huntington's disease: a retrospective cohort analysis
|
discussion
|
discussion
|
[
1,
2,
3,
4,
5,
6
] |
[
355710,
355711,
355712
] |
[
50818,
50819,
50820,
50821,
50822
] |
Assuming that the mean detection window of the virus can be informed by the mean serial interval, here set at 7.5 days [3] (Table 1), the ascertainment rate was estimated to be 9.2% (95% confidence interval [CI]: 5.0, 20.0).
| 3
|
[
355711,
50820
] |
PMC7074297
|
PMC7121484
|
The Rate of Underascertainment of Novel Coronavirus (2019-nCoV) Infection: Estimation Using Japanese Passengers Data on Evacuation Flights
|
Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus–Infected Pneumonia
|
estimate of the incidence of “infection”
|
results/conclusion
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12
] |
[
361493,
361494,
361495,
361496,
361497
] |
[
50810,
50811
] |
Based upon preliminary reports on COVID-19 [6], the quarantine time was established at 14 days.
| 6
|
[
361493,
50811
] |
PMC7102645
|
PMC7121484
|
Testing the repatriated for SARS-Cov2: Should laboratory-based quarantine replace traditional quarantine?
|
Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus–Infected Pneumonia
|
laboratory testing
|
laboratory testing
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22
] |
[
361537,
361538,
361539,
361540,
361541
] |
[
357551,
357552,
357553,
357554,
357555,
357556,
357557,
357558
] |
[11]China1099 (173 severe)47 (median)41.9%168 (132–207)172 (139–212)137.5 (99.0–179.5)36.2%31.6%57.7%Huang et al.
| 11
|
[
361537,
357557
] |
PMC7102663
|
PMC7092819
|
Thrombocytopenia is associated with severe coronavirus disease 2019 (COVID-19) infections: A meta-analysis
|
Clinical Characteristics of Coronavirus Disease 2019 in China
|
statistical analysis
|
participants
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22
] |
[
361537,
361538,
361539,
361540,
361541
] |
[
357551,
357552,
357553,
357554,
357555,
357556,
357557,
357558
] |
[11], which accounted for nearly 71% of the overall sample size.
| 11
|
[
361537,
357557
] |
PMC7102663
|
PMC7092819
|
Thrombocytopenia is associated with severe coronavirus disease 2019 (COVID-19) infections: A meta-analysis
|
Clinical Characteristics of Coronavirus Disease 2019 in China
|
statistical analysis
|
participants
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22
] |
[
361546
] |
[
82970
] |
[10].
| 10
|
[
361546,
82970
] |
PMC7102663
|
PMC1097734
|
Thrombocytopenia is associated with severe coronavirus disease 2019 (COVID-19) infections: A meta-analysis
|
Estimating the mean and variance from the median, range, and the size of a sample
|
competing interests
|
competing interests
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15
] |
[
366310,
366311,
366312,
366313,
366314
] |
[
373809,
373810,
373811,
373812
] |
Altered socioeconomic status (unemployment), household stress, anxiety, depression, and the deprivation of social contacts have already been reported [14], and they are also major risk factors for cardiovascular disease, particularly in the elderly.
| 14
|
[
366310,
373809
] |
PMC7146013
|
PMC7195292
|
Perspective: cardiovascular disease and the Covid-19 pandemic
|
The emotional impact of Coronavirus 2019-nCoV (new Coronavirus disease)
|
participants
|
abstract
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18
] |
[
366456
] |
[
365359,
365360,
365361,
365362,
365363,
365364
] |
New coronavirus pneumonia (COVID-19) is a health emergency due to its high infectiousness [1] and high case fatality in critically ill patients.
| 1
|
[
366456,
365364
] |
PMC7146693
|
PMC7135076
|
C-reactive protein levels in the early stage of COVID-19
|
Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study
|
funding
|
participants
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10
] |
[
371312,
371313,
371314,
371315,
371316,
371317
] |
[
362017,
362018,
362019,
362020,
362021,
362022,
362023,
362024,
362025
] |
[6], the mortality rate was high (5/13) leading the authors to alert the scientific community and to postpone elective surgery interventions.
| 6
|
[
371313,
362018
] |
PMC7183971
|
PMC7104422
|
Nosocomial infection with SARS-Cov-2 within Departments of Digestive Surgery
|
Clinical and Transmission Characteristics of Covid-19 — A Retrospective Study of 25 Cases from a Single Thoracic Surgery Department
|
results/conclusion
|
abstract
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10
] |
[
371312,
371313,
371314,
371315,
371316,
371317
] |
[
362017,
362018,
362019,
362020,
362021,
362022,
362023,
362024,
362025
] |
For the hospital community, there is a risk is of transforming a so-called COVID-19–service into a COVID-19+ service [6].
| 6
|
[
371313,
362018
] |
PMC7183971
|
PMC7104422
|
Nosocomial infection with SARS-Cov-2 within Departments of Digestive Surgery
|
Clinical and Transmission Characteristics of Covid-19 — A Retrospective Study of 25 Cases from a Single Thoracic Surgery Department
|
results/conclusion
|
abstract
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9
] |
[
373827,
373828,
373829
] |
[
50390,
50391,
50392,
50393,
50394
] |
On 31 December 2019, the Chinese Center for Disease Control and Prevention reported to the World Health Organization (WHO) a series of patients with pneumonia of uncertain aetiology in Wuhan city, Hubei province, China [1].
| 1
|
[
373828,
50391
] |
PMC7195305
|
PMC7092803
|
Interpret with caution: An evaluation of the commercial AusDiagnostics versus in-house developed assays for the detection of SARS-CoV-2 virus
|
A Novel Coronavirus from Patients with Pneumonia in China, 2019
|
genome sequencing
|
viral genome sequencing
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18
] |
[
375122,
375123,
375124
] |
[
383208,
383209
] |
[16], which estimated a mean of 3.96 days (95% CI: 3.53–4.39) and a SD of 4.75 days (95% CI: 4.46–5.07).
| 16
|
[
375123,
383208
] |
PMC7201952
|
PMC7258488
|
Estimating the generation interval for coronavirus disease (COVID-19) based on symptom onset data, March 2020
|
Serial Interval of COVID-19 among Publicly Reported Confirmed Cases
|
introduction
|
abstract
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18
] |
[
375122,
375123,
375124
] |
[
50812,
50813,
50814,
50815,
50816
] |
[3] estimated the basic reproduction number using a renewal equation to be 2.2 (95% confidence interval (CI): 1.4–3.9), the serial interval distribution to have a mean of 7.5 days (95% CI: 5.3–19) based on six observations, and the incubation period distribution to have a mean of 5.2 days (95% CI: 4.1–7.0) based on 10 observations.
| 3
|
[
375124,
50812
] |
PMC7201952
|
PMC7121484
|
Estimating the generation interval for coronavirus disease (COVID-19) based on symptom onset data, March 2020
|
Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus–Infected Pneumonia
|
introduction
|
statistical analysis
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22,
23,
24,
25,
26,
27,
28,
29,
30,
31,
32,
33,
34,
35,
36,
37,
38,
39,
40,
41,
42,
43,
44,
45,
46,
47,
48,
49,
50,
51,
52,
53,
54,
55,
56,
57
] |
[
375756,
375757,
375758,
375759
] |
[
364998,
364999
] |
En France, les établissements autorisés en psychiatrie ont très rapidement créé des unités permettant de prendre en charge les patients souffrant de troubles psychiatriques et du Covid-19 [28].
| 28
|
[
375756,
364999
] |
PMC7205690
|
PMC7130411
|
Prisons confinées : quelles conséquences pour les soins psychiatriques et la santé mentale des personnes détenues en France ?
|
Assurer les soins aux patients souffrant de troubles psychiques en France pendant l’épidémie à SARS-CoV-2
|
les soins psychiatriques de niveaux 1 et 2
|
abstract
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22,
23,
24,
25,
26,
27,
28,
29,
30,
31,
32,
33,
34,
35,
36,
37,
38,
39,
40,
41,
42,
43,
44,
45,
46,
47,
48,
49,
50,
51,
52,
53,
54,
55,
56,
57
] |
[
375764,
375765
] |
[
356978,
356979,
356980,
356981
] |
Les rares données actuellement disponibles en population générale font état de phénomènes fréquents de peur de la contamination, d’inquiétude pour les proches, d’irritabilité ou de sentiments de frustration et d’impuissance [41].
| 41
|
[
375764,
356981
] |
PMC7205690
|
PMC7084952
|
Prisons confinées : quelles conséquences pour les soins psychiatriques et la santé mentale des personnes détenues en France ?
|
Immediate Psychological Responses and Associated Factors during the Initial Stage of the 2019 Coronavirus Disease (COVID-19) Epidemic among the General Population in China
|
le poids du confinement en détention
|
results/conclusion
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11
] |
[
381020,
381021,
381022
] |
[
85650,
85651,
85652,
85653,
85654,
85655,
85656
] |
& UG) using an online platform (“Online surveys” [formerly BOS-Bristol Online Survey], developed by the University of Bristol) in accordance with the Checklist for Reporting Results of Internet E-Surveys (the CHERRIES statement) [8].
| 8
|
[
381020,
85653
] |
PMC7242177
|
PMC1550605
|
Impact of COVID-19 Outbreak on Healthcare Workers in Italy: Results from a National E-Survey
|
Improving the Quality of Web Surveys: The Checklist for Reporting Results of Internet E-Surveys (CHERRIES)
|
statistical analysis
|
introduction
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22,
23,
24,
25,
26,
27,
28,
29,
30,
31,
32,
33,
34,
35,
36,
37,
38,
39,
40,
41,
42,
43,
44,
45,
46,
47,
48,
49,
50,
51,
52,
53,
54,
55,
56,
57,
58,
59,
60,
61,
62,
63,
64,
65,
66,
67,
68,
69,
70,
71,
72,
73,
74,
75,
76,
77
] |
[
382213,
382214,
382215,
382216
] |
[
361740,
361741,
361742,
361743,
361744,
361745
] |
Based on epidemiological data of confirmed MERS cases reported to the WHO from September 2012 to 2 June 2018, Amgad A Elkholy and colleagues [25] found there were 415 HCW MERS cases globally by conducting a retrospective analysis.
| 25
|
[
382214,
361740
] |
PMC7250777
|
PMC7102841
|
SARS, MERS and COVID-19 among healthcare workers: A narrative review
|
MERS-CoV infection among healthcare workers and risk factors for death: Retrospective analysis of all laboratory-confirmed cases reported to WHO from 2012 to 2 June 2018
|
mers among hcws
|
abstract
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22,
23,
24,
25,
26,
27,
28,
29,
30,
31,
32,
33,
34,
35,
36,
37,
38,
39,
40,
41,
42,
43,
44,
45,
46,
47,
48,
49,
50,
51,
52,
53,
54,
55,
56,
57,
58,
59,
60,
61,
62,
63,
64,
65,
66,
67,
68,
69,
70,
71,
72,
73,
74,
75,
76,
77
] |
[
382213,
382214,
382215,
382216
] |
[
361740,
361741,
361742,
361743,
361744,
361745
] |
By conducting a retrospective analysis based on the epidemiological data of confirmed MERS cases reported to the WHO from September 2012 to 2 June 2018, Elkholy and colleagues [25] reported the fatality rate of HCW MERS cases is 5.78% (24/415), which is far lower than that of the non-HCWs.
| 25
|
[
382214,
361740
] |
PMC7250777
|
PMC7102841
|
SARS, MERS and COVID-19 among healthcare workers: A narrative review
|
MERS-CoV infection among healthcare workers and risk factors for death: Retrospective analysis of all laboratory-confirmed cases reported to WHO from 2012 to 2 June 2018
|
mers among hcws
|
abstract
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22,
23,
24,
25,
26,
27,
28,
29,
30,
31,
32,
33,
34,
35,
36,
37,
38,
39,
40,
41,
42,
43,
44,
45,
46,
47,
48,
49,
50,
51,
52,
53,
54,
55,
56,
57,
58,
59,
60,
61,
62,
63,
64,
65,
66,
67,
68,
69,
70,
71,
72,
73,
74,
75,
76,
77
] |
[
382217,
382218,
382219,
382220,
382221,
382222,
382223,
382224
] |
[
357551,
357552,
357553,
357554,
357555,
357556,
357557,
357558
] |
By extracting data regarding 1099 patients with laboratory-confirmed COVID-19, Guan and colleagues found a total of 3.5% (about 38 of 1099) confirmed cases are HCWs [29].
| 29
|
[
382218,
357551
] |
PMC7250777
|
PMC7092819
|
SARS, MERS and COVID-19 among healthcare workers: A narrative review
|
Clinical Characteristics of Coronavirus Disease 2019 in China
|
covid-19 among hcws
|
participants
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21
] |
[
386620,
386621,
386622,
386623
] |
[
356356,
356357,
356358,
356359
] |
Certainly, inflammatory cytokine storm and viral evasion of cellular immune responses play a central role in disease progression and severity [7].
| 7
|
[
386623,
356359
] |
PMC7282743
|
PMC7079893
|
Lactate dehydrogenase and C-reactive protein as predictors of respiratory failure in CoVID-19 patients
|
Pathogenic human coronavirus infections: causes and consequences of cytokine storm and immunopathology
|
abstract
|
other immunomodulatory agents
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21
] |
[
386619
] |
[
379327
] |
As reported by Pan et al, chest CT has a pivotal role for the diagnosis and assessment of the severity of lung involvement in COVID-19 pneumonia [19].
| 19
|
[
386619,
379327
] |
PMC7282743
|
PMC7233367
|
Lactate dehydrogenase and C-reactive protein as predictors of respiratory failure in CoVID-19 patients
|
Time Course of Lung Changes On Chest CT During Recovery From 2019 Novel Coronavirus (COVID-19) Pneumonia
|
competing interests
|
funding
|
[
1,
2,
3,
4,
5,
6,
7,
8
] |
[
386645,
386646,
386647,
386648,
386649,
386650
] |
[
392254,
392255,
392256,
392257,
392258
] |
Cross-reactivity may occur in SARS and MERS coronavirus patients, but widespread community spread of these strains is uncommon [6].
| 6
|
[
386645,
392255
] |
PMC7282795
|
PMC7323511
|
Clinical evaluation of serological IgG antibody response on the Abbott Architect for established SARS-CoV-2 infection
|
Severe Acute Respiratory Syndrome Coronavirus 2−Specific Antibody Responses in Coronavirus Disease Patients
|
abstract
|
discussion
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22,
23,
24,
25,
26,
27,
28,
29,
30,
31,
32,
33,
34,
35,
36,
37,
38
] |
[
389411,
389412
] |
[
355509,
355510,
355511
] |
SARS-CoV-2 and SARS-CoV have 79% homology, so the characteristics of the two diseases are similar [28].
| 28
|
[
389411,
355510
] |
PMC7303626
|
PMC7067204
|
Public health initiatives from hospitalized patients with COVID-19, China
|
Genomic characterization of the 2019 novel human-pathogenic coronavirus isolated from a patient with atypical pneumonia after visiting Wuhan
|
participants
|
viral sequences
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22,
23,
24,
25,
26,
27,
28,
29,
30,
31,
32,
33,
34,
35,
36,
37,
38
] |
[
389423,
389424,
389425,
389426,
389427,
389428,
389429,
389430
] |
[
326331,
326332,
326333
] |
For MERS, its tissue tropism is wider than other coronaviruses [24].
| 24
|
[
389430,
326333
] |
PMC7303626
|
PMC6357155
|
Public health initiatives from hospitalized patients with COVID-19, China
|
From SARS to MERS, Thrusting Coronaviruses into the Spotlight
|
discussion
|
1.1. mouse models
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22,
23,
24,
25,
26,
27,
28,
29,
30,
31,
32,
33,
34,
35,
36,
37,
38
] |
[
389411,
389412
] |
[
352812,
352813,
352814,
352815
] |
A noval coronavirus was than isolated from the respiratory epithelium of patients, and the new coronavirus was officially named as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) [3].
| 3
|
[
389412,
352814
] |
PMC7303626
|
PMC6988272
|
Public health initiatives from hospitalized patients with COVID-19, China
|
Real-time tentative assessment of the epidemiological characteristics of novel coronavirus infections in Wuhan, China, as at 22 January 2020
|
participants
|
early information on 2019-ncov infections as at 12 january
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22,
23,
24,
25,
26,
27,
28,
29,
30,
31,
32,
33,
34,
35,
36,
37,
38,
39,
40,
41,
42,
43,
44,
45,
46,
47,
48,
49,
50,
51,
52,
53,
54
] |
[
398086,
398087,
398088
] |
[
392309,
392310
] |
[51].
| 51
|
[
398087,
392310
] |
PMC7368913
|
PMC7323562
|
Determination of an optimal control strategy for vaccine administration in COVID-19 pandemic treatment
|
High Contagiousness and Rapid Spread of Severe Acute Respiratory Syndrome Coronavirus 2
|
inverse problem
|
calculations of r0 and effect of intervention strategies
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22,
23,
24,
25,
26,
27,
28,
29,
30,
31,
32,
33,
34,
35,
36,
37,
38,
39,
40,
41,
42,
43,
44,
45,
46,
47,
48,
49,
50,
51,
52,
53,
54
] |
[
398104
] |
[
50596
] |
[18] used a Susceptible-Infectious-Removed (SIR) model to predict the COVID-19 epidemic in Wuhan after the lockdown and quarantine.
| 18
|
[
398104,
50596
] |
PMC7368913
|
PMC7104073
|
Determination of an optimal control strategy for vaccine administration in COVID-19 pandemic treatment
|
Why is it difficult to accurately predict the COVID-19 epidemic?
|
competing interests
|
competing interests
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22,
23,
24,
25,
26,
27,
28,
29,
30,
31,
32,
33,
34,
35,
36,
37,
38,
39,
40,
41,
42,
43,
44,
45,
46,
47,
48,
49,
50,
51,
52,
53,
54
] |
[
398104
] |
[
50596
] |
[18].
| 18
|
[
398104,
50596
] |
PMC7368913
|
PMC7104073
|
Determination of an optimal control strategy for vaccine administration in COVID-19 pandemic treatment
|
Why is it difficult to accurately predict the COVID-19 epidemic?
|
competing interests
|
competing interests
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22,
23,
24,
25,
26,
27,
28,
29,
30,
31,
32,
33,
34,
35,
36,
37,
38,
39,
40,
41,
42,
43,
44,
45,
46,
47,
48,
49,
50,
51,
52,
53,
54,
55,
56,
57,
58,
59,
60,
61
] |
[
404713
] |
[
204938
] |
During the Ebola outbreak in Sierra Leone, health services were severely affected, and factors such as patients' fear of Ebola and death of healthcare staff affected health-seeking behavior and adversely impacted health service functioning [17].
| 17
|
[
404713,
204938
] |
PMC7428732
|
PMC4318968
|
Impact of COVID-19 pandemic response on uptake of routine immunizations in Sindh, Pakistan: An analysis of provincial electronic immunization registry data
|
Ebola and Indirect Effects on Health Service Function in Sierra Leone
|
competing interests
|
competing interests
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22,
23,
24
] |
[
410995,
410996,
410997,
410998,
410999
] |
[
371388,
371389,
371390,
371391,
371392
] |
The time it takes to develop a vaccine is estimated to be 1 or 1.5 years as different steps are necessary during the clinical development of a vaccine [5].
| 5
|
[
410997,
371391
] |
PMC7498238
|
PMC7184325
|
Intention to participate in a COVID-19 vaccine clinical trial and to get vaccinated against COVID-19 in France during the pandemic
|
Human Challenge Studies to Accelerate Coronavirus Vaccine Licensure
|
willingness to participate in a covid-19 vaccine clinical trial
|
abstract
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22,
23,
24
] |
[
410990,
410991,
410992,
410993,
410994
] |
[
249442,
249443,
249444,
249445,
249446,
249447
] |
This is a particular concern in France, which has been shown to be the leader-country of vaccine hesitancy [8].
| 8
|
[
410990,
249444
] |
PMC7498238
|
PMC5078590
|
Intention to participate in a COVID-19 vaccine clinical trial and to get vaccinated against COVID-19 in France during the pandemic
|
The State of Vaccine Confidence 2016: Global Insights Through a 67-Country Survey
|
willingness to get vaccinated against covid-19
|
abstract
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22,
23,
24,
25,
26,
27,
28,
29,
30
] |
[
411214
] |
[
362837,
362838
] |
[30] conclude that the mean estimate of R 0 ranges from 2.24 (95% CI: 1.96–2.55) to 3.58 (95% CI: 2.89–4.39).
| 30
|
[
411214,
362838
] |
PMC7500883
|
PMC7110798
|
Simulation of coronavirus disease 2019 (COVID-19) scenarios with possibility of reinfection
|
Preliminary estimation of the basic reproduction number of novel coronavirus (2019-nCoV) in China, from 2019 to 2020: A data-driven analysis in the early phase of the outbreak
|
funding
|
disclaimer
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22,
23,
24,
25,
26,
27,
28,
29,
30
] |
[
411198,
411199,
411200,
411201
] |
[
392322,
392323,
392324,
392325
] |
[23] obtain a higher median estimate, R0=5.7(95% CI: 3.8–8.9).
| 23
|
[
411200,
392324
] |
PMC7500883
|
PMC7323562
|
Simulation of coronavirus disease 2019 (COVID-19) scenarios with possibility of reinfection
|
High Contagiousness and Rapid Spread of Severe Acute Respiratory Syndrome Coronavirus 2
|
model
|
estimating r0
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22,
23,
24,
25,
26,
27,
28,
29,
30
] |
[
411198,
411199,
411200,
411201
] |
[
367546,
367547,
367548
] |
[14], Lin et al.
| 14
|
[
411201,
367547
] |
PMC7500883
|
PMC7158569
|
Simulation of coronavirus disease 2019 (COVID-19) scenarios with possibility of reinfection
|
Early dynamics of transmission and control of COVID-19: a mathematical modelling study
|
model
|
methods
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22,
23,
24,
25,
26,
27,
28,
29,
30,
31,
32,
33,
34,
35,
36,
37,
38,
39,
40,
41,
42,
43,
44,
45,
46,
47,
48,
49,
50,
51,
52,
53,
54,
55,
56,
57,
58,
59,
60,
61,
62,
63,
64,
65,
66,
67,
68,
69,
70,
71,
72,
73,
74,
75,
76,
77,
78,
79,
80,
81,
82,
83,
84,
85,
86,
87,
88,
89,
90,
91,
92,
93,
94,
95,
96,
97,
98,
99,
100,
101,
102,
103,
104,
105,
106,
107,
108,
109,
110,
111,
112,
113,
114,
115,
116,
117,
118,
119,
120,
121,
122,
123,
124,
125,
126,
127,
128,
129,
130,
131,
132
] |
[
415609
] |
[
378627
] |
Alternatively, in the antibody test strip, blood samples are collected from patients that contain antibodies to the virus [81].
| 81
|
[
415609,
378627
] |
PMC7543751
|
PMC7228300
|
Current progress on COVID-19 related to biosensing technologies: New opportunity for detection and monitoring of viruses
|
Development and clinical application of a rapid IgM‐IgG combined antibody test for SARS‐CoV‐2 infection diagnosis
|
competing interests
|
competing interests
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22,
23,
24,
25,
26,
27,
28,
29,
30,
31,
32,
33,
34,
35,
36,
37,
38,
39,
40,
41,
42,
43,
44,
45,
46,
47,
48,
49,
50,
51,
52,
53,
54,
55,
56,
57,
58,
59,
60,
61,
62,
63,
64,
65,
66,
67,
68,
69,
70,
71,
72,
73,
74,
75,
76,
77,
78,
79
] |
[
417572
] |
[
366848
] |
Although structural factors were evoked in some cases as moderators of MHD risk [28], no study to date has adequately examined their effect on HCW psychological outcomes.
| 28
|
[
417572,
366848
] |
PMC7560258
|
PMC7151415
|
Assessment of mental health outcomes and associated factors among workers in community-based HIV care centers in the early stage of the COVID-19 outbreak in Mali
|
COVID-19 and mental health: A review of the existing literature
|
competing interests
|
competing interests
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22,
23,
24,
25,
26,
27,
28,
29,
30,
31,
32,
33
] |
[
432014,
432015,
432016,
432017,
432018
] |
[
179877,
179878,
179879
] |
Similarly, conspiracy beliefs about vaccinations can exacerbate vaccination hesitancy [17], and we expected this to be no different for any COVID-19 vaccine that comes to market.
| 17
|
[
432018,
179877
] |
PMC7794597
|
PMC3930676
|
Predictors of intention to vaccinate against COVID-19: Results of a nationwide survey
|
The Effects of Anti-Vaccine Conspiracy Theories on Vaccination Intentions
|
abstract
|
abstract
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14
] |
[
433743,
433744,
433745,
433746
] |
[
394550,
394551,
394552,
394553,
394554,
394555,
394556,
394557
] |
The nationwide Spanish seroepidemiological study ‘ENE-COVID’ concluded that 10% of HCWs in our country had antibodies against SARS-CoV-2, while only 5.2% antibodies were detected in the general population [3].
| 3
|
[
433744,
394556
] |
PMC7814253
|
PMC7336131
|
Risk of contagion of SARS-CoV-2 among otorhinolaryngologists in Spain during the “Two waves”
|
Prevalence of SARS-CoV-2 in Spain (ENE-COVID): a nationwide, population-based seroepidemiological study
|
introduction
|
discussion
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14
] |
[
433743,
433744,
433745,
433746
] |
[
394550,
394551,
394552,
394553,
394554,
394555,
394556,
394557
] |
This rate is three times higher as compared with the general population in Spain with a seroprevalence of 5.2% of IgG antibodies against SARS-Cov2, and also above the 10% rate of antibodies among HCWs found in the same study [3].
| 3
|
[
433744,
394556
] |
PMC7814253
|
PMC7336131
|
Risk of contagion of SARS-CoV-2 among otorhinolaryngologists in Spain during the “Two waves”
|
Prevalence of SARS-CoV-2 in Spain (ENE-COVID): a nationwide, population-based seroepidemiological study
|
introduction
|
discussion
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14
] |
[
433743,
433744,
433745,
433746
] |
[
394550,
394551,
394552,
394553,
394554,
394555,
394556,
394557
] |
Similar results about regional differences were reported in a large nationwide study about seroprevalence of SARS-CoV-2 in Spain (ENE-COVID) [3] with prevalence five times higher in Madrid and central parts of Spain than that observed in low-risk regions.
| 3
|
[
433744,
394556
] |
PMC7814253
|
PMC7336131
|
Risk of contagion of SARS-CoV-2 among otorhinolaryngologists in Spain during the “Two waves”
|
Prevalence of SARS-CoV-2 in Spain (ENE-COVID): a nationwide, population-based seroepidemiological study
|
introduction
|
discussion
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22,
23,
24,
25,
26,
27,
28,
29
] |
[
439949,
439950,
439951,
439952
] |
[
386431
] |
This must be considered a limitation of these rapid immunochromatographic assays taking also into account that Ct values ranging from 20 to 30 are considered normal findings [25].
| 25
|
[
439952,
386431
] |
PMC7897404
|
PMC7278630
|
Salivary SARS-CoV-2 antigen rapid detection: A prospective cohort study
|
Evaluation of rapid antigen test for detection of SARS-CoV-2 virus
|
nps and saliva antigen testing
|
viral culture for sars-cov-2 virus
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21
] |
[
442757,
442758
] |
[
207010
] |
The terms vaccine hesitancy and anti-vaccination, which are connected, yet different ideas have previously been used interchangeably in the literature [10].
| 10
|
[
442757,
207010
] |
PMC7936546
|
PMC4353679
|
Vaccine hesitancy and anti-vaccination in the time of COVID-19: A Google Trends analysis
|
Vaccine Hesitancy: Clarifying a Theoretical Framework for an Ambiguous Notion
|
competing interests
|
competing interests
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21
] |
[
442757,
442758
] |
[
207010
] |
Anti-vaccination is regarded here as the opinions and actions against vaccination use, which itself may be considered a downstream effect of vaccine hesitancy [10].
| 10
|
[
442757,
207010
] |
PMC7936546
|
PMC4353679
|
Vaccine hesitancy and anti-vaccination in the time of COVID-19: A Google Trends analysis
|
Vaccine Hesitancy: Clarifying a Theoretical Framework for an Ambiguous Notion
|
competing interests
|
competing interests
|
[
1,
2,
3,
4,
5,
6
] |
[
448593,
448594,
448595,
448596
] |
[
50416,
50417,
50418,
50419
] |
Six species of coronavirus are already known to cause disease in humans: four viruses 229E, OC43, NL63, and HKU1 are prevalent and cause common cold symptoms in immunocompetent individuals; two other strains, namely, severe acute respiratory syndrome coronavirus (SARS-CoV) and Middle Eastern respiratory syndrome coronavirus (MERS-CoV), are zoonotic in origin and have been linked to sometimes fatal diseases [1].
| 1
|
[
448593,
50416
] |
PMC8070680
|
PMC7092803
|
Detection of SARS-COV-2 Proteins Using an ELISA Test
|
A Novel Coronavirus from Patients with Pneumonia in China, 2019
|
introduction
|
abstract
|
[
1,
2,
3,
4,
5,
6
] |
[
448593,
448594,
448595,
448596
] |
[
356119,
356120
] |
On the “Diamond Princess” cruise ship, which was isolated in Japanese waters in February 2020 due to SARS-CoV-2 infections, an incidence of asymptomatic infections of 51.7% was found [6].
| 6
|
[
448595,
356120
] |
PMC8070680
|
PMC7078829
|
Detection of SARS-COV-2 Proteins Using an ELISA Test
|
Estimating the asymptomatic proportion of coronavirus disease 2019 (COVID-19) cases on board the Diamond Princess cruise ship, Yokohama, Japan, 2020
|
introduction
|
data
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22,
23,
24,
25,
26,
27,
28,
29,
30,
31
] |
[
449169
] |
[
357291
] |
Already before the pandemic, vaccine hesitancy was named as one of the top ten threats to global health in 2019 by the World Health Organization [9], and this issue grew further in light of the COVID-19 pandemic.
| 9
|
[
449169,
357291
] |
PMC8078903
|
PMC7090020
|
COVID-19 vaccine hesitancy and related fears and anxiety
|
Vaccine Safety: Myths and Misinformation
|
competing interests
|
competing interests
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22,
23,
24,
25,
26,
27,
28,
29,
30,
31
] |
[
449112,
449113,
449114,
449115,
449116,
449117,
449118
] |
[
408202,
408203,
408204,
408205
] |
Furthermore, most studies on vaccine acceptance took part before the actual availability of vaccines but this lack needs to be closed because there can be (in congruency with intention-behavior-models) expected a gap between the prospectively hypothetically reported willingness for a behavior (e.g., vaccination) and the attitude in the context of an actually possible vaccination [21].
| 21
|
[
449115,
408202
] |
PMC8078903
|
PMC7459701
|
COVID-19 vaccine hesitancy and related fears and anxiety
|
Key Guidelines in Developing a Pre-Emptive COVID-19 Vaccination Uptake Promotion Strategy
|
introduction
|
introduction
|
[
1,
2,
3,
4,
5,
6,
7,
8
] |
[
20058,
20059,
20060,
20061,
20062
] |
[
369990,
369991,
369992,
369993,
369994
] |
Concerns among responders regarding a potential COVID-19 vaccine provide important targets for possible interventional educational programs to enhance vaccination rates [8].
| 8
|
[
20061,
369991
] |
PMC8851308
|
PMC7174145
|
Vaccine hesitancy: the next challenge in the fight against COVID-19
|
Vaccine confidence in the time of COVID-19
|
abstract
|
abstract
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13
] |
[
22294,
22295,
22296,
22297,
22298,
22299
] |
[
19944,
19945,
19946,
19947,
19948
] |
Methods of selecting eligible subjects were described in the preceding study [5].
| 5
|
[
22297,
19944
] |
PMC9140418
|
PMC8834809
|
Shorter Incubation Period among COVID-19 Cases with the BA.1 Omicron Variant
|
Shorter Incubation Period among Unvaccinated Delta Variant Coronavirus Disease 2019 Patients in Japan
|
discussion
|
abstract
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13
] |
[
22294,
22295,
22296,
22297,
22298,
22299
] |
[
19944,
19945,
19946,
19947,
19948
] |
Our preceding study using contact tracing data estimated the median incubation period of the Delta variant was 3.7 days (95%CI = 3.3–3.7) [5].
| 5
|
[
22297,
19944
] |
PMC9140418
|
PMC8834809
|
Shorter Incubation Period among COVID-19 Cases with the BA.1 Omicron Variant
|
Shorter Incubation Period among Unvaccinated Delta Variant Coronavirus Disease 2019 Patients in Japan
|
discussion
|
abstract
|
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13
] |
[
22294,
22295,
22296,
22297,
22298,
22299
] |
[
205690,
205691,
205692
] |
We estimated median incubation time and important quantiles (5.0th, 25th, 75th and 95th percentiles) with a 95% confidence interval (CI) by fitting the parametric log-normal distribution in a Bayesian framework because this statistical technique for assessing incubation periods has been used for many other acute respiratory viral infections [8].
| 8
|
[
22299,
205692
] |
PMC9140418
|
PMC4327893
|
Shorter Incubation Period among COVID-19 Cases with the BA.1 Omicron Variant
|
Incubation periods of acute respiratory viral infections: a systematic review
|
discussion
|
abstract
|
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