scholarly journals Timely surveillance and temporal calibration of disease response against human infectious diseases

PLoS ONE ◽  
2021 ◽  
Vol 16 (10) ◽  
pp. e0258332
Author(s):  
Kamran Najeebullah ◽  
Jessica Liebig ◽  
Jonathan Darbro ◽  
Raja Jurdak ◽  
Dean Paini
Keyword(s):  
Disease Surveillance ◽  
Reproduction Number ◽  
Disease Spread ◽  
High Morbidity ◽  
Dengue Case ◽  
Response Delay ◽  
Effective Response ◽  
Disease Response ◽  
Awareness Campaigns ◽  
Outbreak Size

Background Disease surveillance and response are critical components of epidemic preparedness. The disease response, in most cases, is a set of reactive measures that follow the outcomes of the disease surveillance. Hence, timely surveillance is a prerequisite for an effective response. Methodology/principal findings We apply epidemiological soundness criteria in combination with the Latent Influence Point Process and time-to-event models to construct a disease spread network. The network implicitly quantifies the fertility (whether a case leads to secondary cases) and reproduction (number of secondary cases per infectious case) of the cases as well as the size and generations (of the infection chain) of the outbreaks. We test our approach by applying it to historic dengue case data from Australia. Using the data, we empirically confirm that high morbidity relates positively with delay in disease response. Moreover, we identify what constitutes timely surveillance by applying various thresholds of disease response delay to the network and report their impact on case fertility, reproduction, number of generations and ultimately, outbreak size. We observe that enforcing a response delay threshold of 5 days leads to a large average reduction across all parameters (occurrence 87%, reproduction 83%, outbreak size 80% and outbreak generations 47%), whereas extending the threshold to 10 days, in comparison, significantly limits the effectiveness of the response actions. Lastly, we identify the components of the disease surveillance system that can be calibrated to achieve the identified thresholds. Conclusion We identify practically achievable, timely surveillance thresholds (on temporal scale) that lead to an effective response and identify how they can be satisfied. Our approach can be utilized to provide guidelines on spatially and demographically targeted resource allocation for public awareness campaigns as well as to improve diagnostic abilities and turn-around times for the doctors and laboratories involved.

scholarly journals Efficient Surveillance and Temporal Calibration of Disease Response

2021 ◽  
Author(s):  
Kamran Najeebullah ◽  
Jessica Liebig ◽  
Jonathan Darbro ◽  
Raja Jurdak ◽  
Dean Paini
Keyword(s):  
Surveillance System ◽  
Disease Surveillance ◽  
Reproduction Number ◽  
Public Awareness ◽  
Temporal Scale ◽  
Effective Response ◽  
Disease Response ◽  
Awareness Campaigns ◽  
Disease Surveillance System ◽  
Epidemiological Characteristics

AbstractBackgroundDisease surveillance and response are critical components of epidemic preparedness. The disease response, in most cases, is a set of reactive measures that follow the outcomes of the disease surveillance. Hence, efficient surveillance is a prerequisite for an effective response.Methodology/Principal FindingsWe introduce the principle of epidemiological soundness and utilize it to construct a disease spread network. The network implicitly quantifies the fertility (whether a case leads to secondary cases) and reproduction (number of secondary cases per infectious case) of the cases as well as the size and generations (of the infection chain) of the outbreaks. We empirically confirm that high morbidity relates positively with delay in disease response. Moreover, we identify what constitutes efficient surveillance by applying various thresholds of disease response delay to the network and report their impact on case fertility, reproduction, number of generations and ultimately, outbreak size. Lastly, we identify the components of the disease surveillance system that can be calibrated to achieve the identified efficiency thresholds.ConclusionWe identify practically achievable, efficient surveillance thresholds (on temporal scale) that lead to an effective response and identify how they can be satisfied. Our approach can be utilized to provide guidelines on spatially and demographically targeted resource allocation for public awareness campaigns as well as to improve diagnostic abilities and turn-around times for the doctors and laboratories involved.Author SummaryEfficient surveillance and effective response capabilities are pivotal to the prevention and control of the infectious diseases. The disease response is a set of reactive actions that follow the outcomes of the disease surveillance. Ergo, efficient surveillance is a perquisite for the deployment of an effective response. The quantification of the efficiency of a disease surveillance system largely depends on the epidemiological characteristics of the disease. In this paper, we introduce an approach that builds on these characteristics and measures the performance of a disease surveillance system through its impact on the incidence of the disease. Using this approach, we obtain quantitative (on a temporal scale) efficient surveillance thresholds, which if followed by a timely response, lead to a considerable reduction in the disease incidence. Furthermore, we show that these thresholds are practically achievable by identifying the obstacles that lead to less than efficient surveillance outcomes. Our approach can be applied to obtain guidelines on spatially, temporally and demographically targeted resource allocations for public awareness campaigns as well to improve diagnostic ability and turn-around times in treating doctors and pathology labs.

NUMERICAL AND STABILITY ANALYSIS OF THE TRANSMISSION DYNAMICS OF SVIR EPIDEMIC MODEL WITH STANDARD INCIDENCE RATE

2019 ◽  
Vol 4 (2) ◽  
pp. 349 ◽  
Author(s):  
Oluwatayo Michael Ogunmiloro ◽  
Fatima Ohunene Abedo ◽  
Hammed Kareem
Keyword(s):  
Reproduction Number ◽  
Disease Spread ◽  
Asymptotically Stable ◽  
Equilibrium Solutions ◽  
Transform Method ◽  
Globally Asymptotically Stable ◽  
Differential Transform ◽  
Mathematical Techniques ◽  
Fourth Order Method ◽  
Theoretical Results

In this article, a Susceptible – Vaccinated – Infected – Recovered (SVIR) model is formulated and analysed using comprehensive mathematical techniques. The vaccination class is primarily considered as means of controlling the disease spread. The basic reproduction number (Ro) of the model is obtained, where it was shown that if Ro<1, at the model equilibrium solutions when infection is present and absent, the infection- free equilibrium is both locally and globally asymptotically stable. Also, if Ro>1, the endemic equilibrium solution is locally asymptotically stable. Furthermore, the analytical solution of the model was carried out using the Differential Transform Method (DTM) and Runge - Kutta fourth-order method. Numerical simulations were carried out to validate the theoretical results. 

scholarly journals Variation in human mobility and its impact on the risk of future COVID-19 outbreaks in Taiwan

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Meng-Chun Chang ◽  
Rebecca Kahn ◽  
Yu-An Li ◽  
Cheng-Sheng Lee ◽  
Caroline O. Buckee ◽  
...  
Keyword(s):  
Disease Surveillance ◽  
Initial Conditions ◽  
Human Mobility ◽  
Human Movement ◽  
Disease Spread ◽  
Spatial Spread ◽  
Movement Data ◽  
Intercity Travel ◽  
Travel Restrictions ◽  
The Impact

Abstract Background As COVID-19 continues to spread around the world, understanding how patterns of human mobility and connectivity affect outbreak dynamics, especially before outbreaks establish locally, is critical for informing response efforts. In Taiwan, most cases to date were imported or linked to imported cases. Methods In collaboration with Facebook Data for Good, we characterized changes in movement patterns in Taiwan since February 2020, and built metapopulation models that incorporate human movement data to identify the high risk areas of disease spread and assess the potential effects of local travel restrictions in Taiwan. Results We found that mobility changed with the number of local cases in Taiwan in the past few months. For each city, we identified the most highly connected areas that may serve as sources of importation during an outbreak. We showed that the risk of an outbreak in Taiwan is enhanced if initial infections occur around holidays. Intracity travel reductions have a higher impact on the risk of an outbreak than intercity travel reductions, while intercity travel reductions can narrow the scope of the outbreak and help target resources. The timing, duration, and level of travel reduction together determine the impact of travel reductions on the number of infections, and multiple combinations of these can result in similar impact. Conclusions To prepare for the potential spread within Taiwan, we utilized Facebook’s aggregated and anonymized movement and colocation data to identify cities with higher risk of infection and regional importation. We developed an interactive application that allows users to vary inputs and assumptions and shows the spatial spread of the disease and the impact of intercity and intracity travel reduction under different initial conditions. Our results can be used readily if local transmission occurs in Taiwan after relaxation of border control, providing important insights into future disease surveillance and policies for travel restrictions.

Data-driven tools for assessing and combating COVID-19 outbreaks in Brazil based on analytics and statistical methods

2021 ◽  
Keyword(s):  
Data Analytics ◽  
Exploratory Data Analysis ◽  
Reproduction Number ◽  
Healthcare Systems ◽  
Regional Level ◽  
Data Driven ◽  
Effective Response ◽  
Reproduction Numbers ◽  
Exploratory Data ◽  
Using Data

The COVID-19 pandemic is one of the worst public health crises in Brazil and the world that has ever been faced. One of the main challenges that the healthcare systems have when decision-making is that the protocols tested in other epidemics do not guarantee success in controlling the spread of COVID-19, given its complexity. In this context, an effective response to guide the competent authorities in adopting public policies to fight COVID-19 depends on thoughtful analysis and effective data visualization, ideally based on different data sources. In this paper, we discuss and provide tools that can be helpful using data analytics to respond to the COVID-19 outbreak in Recife, Brazil. We use exploratory data analysis and inferential study to determine the trend changes in COVID-19 cases and their effective or instantaneous reproduction numbers. According to the data obtained of confirmed COVID-19 cases disaggregated at a regional level in this zone, we note a heterogeneous spread in most megaregions in Recife, Brazil. When incorporating quarantines decreed, effectiveness is detected in the regions. Our results indicate that the measures have effectively curbed the spread of the disease in Recife, Brazil. However, other factors can cause the effective reproduction number to not be within the expected ranges, which must be further studied.

scholarly journals Mathematical Analysis of Influenza A Dynamics in the Emergence of Drug Resistance

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Caroline W. Kanyiri ◽  
Kimathi Mark ◽  
Livingstone Luboobi
Keyword(s):  
Mathematical Model ◽  
Sensitivity Analysis ◽  
Drug Resistance ◽  
Stability Analysis ◽  
Influenza A ◽  
Reproduction Number ◽  
Critical Value ◽  
Backward Bifurcation ◽  
Transmission Dynamics ◽  
High Morbidity

Every year, influenza causes high morbidity and mortality especially among the immunocompromised persons worldwide. The emergence of drug resistance has been a major challenge in curbing the spread of influenza. In this paper, a mathematical model is formulated and used to analyze the transmission dynamics of influenza A virus having incorporated the aspect of drug resistance. The qualitative analysis of the model is given in terms of the control reproduction number,Rc. The model equilibria are computed and stability analysis carried out. The model is found to exhibit backward bifurcation prompting the need to lowerRcto a critical valueRc∗for effective disease control. Sensitivity analysis results reveal that vaccine efficacy is the parameter with the most control over the spread of influenza. Numerical simulations reveal that despite vaccination reducing the reproduction number below unity, influenza still persists in the population. Hence, it is essential, in addition to vaccination, to apply other strategies to curb the spread of influenza.

scholarly journals How effective are governmental and university campaigns for increasing meningitis vaccine uptake?

2021 ◽  
Author(s):  
Ayushi Ramjee ◽  
Chloe Ogilvie ◽  
Africa Couto ◽  
Teresa Matini ◽  
Claudia Anaele ◽  
...  
Keyword(s):  
Student Perceptions ◽  
Vaccine Uptake ◽  
Disease Spread ◽  
Awareness Campaigns ◽  
Department Of Health ◽  
Behavioural Patterns ◽  
Health And Social Care ◽  
Catchment Areas ◽  
Student Cohorts ◽  
E Mail

ObjectivesUniversity student cohorts have a potential for significant impacts on public health policies. Health impacts arise from wide geographic catchment areas and behavioural patterns that enhance infectious disease spread and occasional cases of meningococcal meningitis and septicaemia, measles and mumps. Universities and the Department of Health and Social Care have tackled these serious problems through advertising campaigns and by offering free MenACWY and MMR vaccines to university students. Our study aimed to assess the engagement of universities with these vaccine campaigns and student awareness of this information. Study DesignInformation was accrued by a combination of e-mail and telephone interactions with welfare officers at universities. Student perceptions of meningitis vaccine campaigns were studied through use of questionnaires with University of Leicester students. ResultsInformation provided by 17 universities indicated that all universities run meningitis awareness campaigns whereas on campus meningitis campaigns were infrequent and of variable penetration into student cohorts. Assessment of 272 students from a 2019-2020 cohort found that 17.5% and 58% of students did not know or had not had the MMR and MenACWY vaccines. Only 37% of students were aware that these vaccines were free and available from a university-linked GP practice with lack of this knowledge being significantly associated with uncertainty or perceived absence of immunisation. This latter group were significantly associated with a preference for on campus immunisation. DiscussionThis information is important for understanding how to target a critical cohort with effective campaigns for uptake of meningitis, MMR and COVID-19 vaccines.

scholarly journals Investigating the Impact of Asymptomatic Carriers on COVID-19 Transmission

2020 ◽  
Author(s):  
Jacob B. Aguilar ◽  
Jeremy Samuel Faust ◽  
Lauren M. Westafer ◽  
Juan B. Gutierrez
Keyword(s):  
Disease Surveillance ◽  
Reproduction Number ◽  
Clinical Symptoms ◽  
Communicable Disease ◽  
Average Rate ◽  
Point Estimate ◽  
Surveillance Systems ◽  
Average Case ◽  
Asymptomatic Carriers ◽  
The Impact

Coronavirus disease 2019 (COVID-19) is a novel human respiratory disease caused by the SARS-CoV-2 virus. Asymptomatic carriers of the virus display no clinical symptoms but are known to be contagious. Recent evidence reveals that this sub-population, as well as persons with mild disease, are a major contributor in the propagation of COVID-19. The asymptomatic sub-population frequently escapes detection by public health surveillance systems. Because of this, the currently accepted estimates of the basic reproduction number (ℛ0) of the disease are inaccurate. It is unlikely that a pathogen can blanket the planet in three months with an ℛ0 in the vicinity of 3, as reported in the literature (1–6). In this manuscript, we present a mathematical model taking into account asymptomatic carriers. Our results indicate that an initial value of the effective reproduction number could range from 5.5 to 25.4, with a point estimate of 15.4, assuming mean parameters. The first three weeks of the model exhibit exponential growth, which is in agreement with average case data collected from thirteen countries with universal health care and robust communicable disease surveillance systems; the average rate of growth in the number of reported cases is 23.3% per day during this period.

Implementation of Power Law Network Models of Epidemic Surveillance Data for Better Evaluation of Outbreak Detection Alarms

2019 ◽  
Vol 0 (0) ◽  
Author(s):  
Razvan G. Romanescu ◽  
Rob Deardon
Keyword(s):  
Power Law ◽  
Disease Surveillance ◽  
Incidence Rates ◽  
Rate Of Change ◽  
Outbreak Detection ◽  
Disease Spread ◽  
Infectious Period ◽  
Contact Network ◽  
Human Populations ◽  
Susceptible Population

Abstract Properties of statistical alarms have been well studied for simple disease surveillance models, such as normally distributed incidence rates with a sudden or gradual shift in mean at the start of an outbreak. It is known, however, that outbreak dynamics in human populations depend significantly on the heterogeneity of the underlying contact network. The rate of change in incidence for a disease such as influenza peaks early on during the outbreak, when the most highly connected individuals get infected, and declines as the average number of connections in the remaining susceptible population drops. Alarm systems currently in use for detecting the start of influenza seasons generally ignore this mechanism of disease spread, and, as a result, will miss out on some early warning signals. We investigate the performance of various alarms on epidemics simulated from an undirected network model with a power law degree distribution for a pathogen with a relatively short infectious period. We propose simple custom alarms for the disease system considered, and show that they can detect a change in the process sooner than some traditional alarms. Finally, we test our methods on observed rates of influenza-like illness from two sentinel providers (one French, one Spanish) to illustrate their use in the early detection of the flu season.

Sequence Impact Of Pomalidomide and Carfilzomib On Treatment Response In Relapsed Multiple Myeloma

Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 1954-1954 ◽  
Author(s):  
Tomer M Mark ◽  
John N. Allan ◽  
Angelique Boyer ◽  
Adriana C Rossi ◽  
Roger N Pearse ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Partial Response ◽  
Board Of Directors ◽  
Research Funding ◽  
Complete Response ◽  
Salvage Chemotherapy ◽  
Advisory Committees ◽  
Effective Response ◽  
Disease Response ◽  
Prior Therapy

Abstract Background Pomalidomide and Carfilzomib (Cfz) are two recently approved agents for the treatment of multiple myeloma (MM) that has relapsed after prior therapy including an IMiD and bortezomib. The sequencing of these agents to achieve maximum tumor reduction is thus far not known. We have previously reported response data from the combination clarithromycin, pomalidomide, dexamethasone (ClaPD) for relapsed or refractory MM. (Mark et al, ASH 2012). We examined the subset of these patients that had received a Cfz-based regimen prior to ClaPD as well as the subset of patients that received a Cfz-based regimen after ClaPD to determine whether the sequence of agents had any impact on response. Methods One hundred nineteen patients with heavily pretreated RRMM were enrolled into a single-institution study to investigate the effectiveness and tolerability of ClaPD. Eligible subjects had at least 3 prior lines of therapy, one line of which must have included lenalidomide. ClaPD is clarithromycin 500mg twice daily; pomalidomide 4mg for days 1-21, and dexamethasone 40mg on days 1,8,15,22 of a 28-day cycle. Two subsets of patients were compared: 1) Subjects that had received treatment with a Cfz-based prior to ClaPD (CP) and 2) Subjects that had received a Cfz-based therapy after progression on ClaPD (PC). Disease response evaluation was performed monthly with immunoelectrophoresis and free light chain analysis; bone marrow biopsy with skeletal imaging was used to confirm MM progression or complete response (CR). Results Fourteen patients comprised CP and 20 in PC. Patients in the CP group were more heavily pre-treated with a median of 6 (range 3-15) lines of therapy, as compared to 5 lines (range 3-10) for PC. Responses are shown in Table 1. Median cycles of ClaPD and Cfz received in PC was 6.5 (range 2-16) and 5 (1-14), respectively. Median cycles of Cfz and ClaPD in the CP group was 8 (1-19) and 5 (1-23), respectively. CR complete response; VGPR: very good partial response; PR: partial response; SD: stable disease; PD: progressive disease; ORR: overall response rate Conclusions ClaPD and a Cfz-based regimen appear to have equally effective response regardless of sequence in salvage chemotherapy. Somewhat deeper responses are seen with ClaPD after Cfz as compared to Cfz after ClaPD, which is intriguing given that the CP group had more prior lines of treatment than PC. Longer follow-up to analyze duration of the response is needed prior to concluding which sequence (PC vs CP) is more effective. This data supports the use of pomalidomide after carfilzomib failure and vice-versa as potent salvage therapeutic options. Disclosures: Mark: Celgene: Consultancy, Honoraria, Membership on an entity’s Board of Directors or advisory committees, Research Funding, Speakers Bureau; Millennium: Membership on an entity’s Board of Directors or advisory committees, Speakers Bureau; Onyx: Research Funding, Speakers Bureau. Rossi:Celgene: Speakers Bureau. Zafar:Celgene: Speakers Bureau; Millennium: Speakers Bureau; Onyx: Speakers Bureau. Pekle:Celgene: Speakers Bureau; Millennium: Speakers Bureau. Niesvizky:Millennium: The Takeda Oncology Company: Consultancy, Honoraria, Membership on an entity’s Board of Directors or advisory committees, Research Funding, Speakers Bureau; Onyx: Consultancy, Honoraria, Research Funding, Speakers Bureau; Celgene: Consultancy, Honoraria, Membership on an entity’s Board of Directors or advisory committees, Research Funding, Speakers Bureau.

THE DYNAMICS OF A DISCRETE SEIT MODEL WITH AGE AND INFECTION AGE STRUCTURES

2012 ◽  
Vol 05 (03) ◽  
pp. 1260004 ◽  
Author(s):  
HUI CAO ◽  
YANNI XIAO ◽  
YICANG ZHOU
Keyword(s):  
Reproduction Number ◽  
Endemic Equilibrium ◽  
Disease Spread ◽  
Threshold Parameter ◽  
Infection Age ◽  
The Stability ◽  
Globally Stable ◽  
Disease Free ◽  
The Basic Reproduction Number ◽  
Age Structures

Age and infection age have significant influence on the transmission of infectious diseases, such as HIV/AIDS and TB. A discrete SEIT model with age and infection age structures is formulated to investigate the dynamics of the disease spread. The basic reproduction number R0 is defined and used as the threshold parameter to characterize the disease extinction or persistence. It is shown that the disease-free equilibrium is globally stable if R0 < 1, and it is unstable if R0 > 1. When R0 > 1, there exists an endemic equilibrium, and the disease is uniformly persistent. The stability of the endemic equilibrium is investigated numerically.

Sign in / Sign up

Export Citation Format

Share Document