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1.
Lancet Planet Health ; 5(12): e921-e928, 2021 12.
Article in English | MEDLINE | ID: covidwho-1565676

ABSTRACT

In low-income and middle-income countries, such as those in sub-Saharan Africa and Latin America, the COVID-19 pandemic has had substantial implications for women's wellbeing. Policy responses to the COVID-19 pandemic have highlighted the gendered aspect of pandemics; however, addressing the gendered implications of the COVID-19 pandemic comprehensively and effectively requires a planetary health perspective that embraces systems thinking to inequalities. This Viewpoint is based on collective reflections from research done by the authors on COVID-19 responses by international and regional organisations, and national governments, in Latin America and sub-Saharan Africa between June, 2020, and June, 2021. A range of international and regional actors have made important policy recommendations to address the gendered implications of the COVID-19 pandemic on women's health and wellbeing since the start of the pandemic. However, national-level policy responses to the COVID-19 pandemic have been partial and inconsistent with regards to gender in both sub-Saharan Africa and Latin America, largely failing to recognise the multiple drivers of gendered health inequalities. This Viewpoint proposes that addressing the effects of the COVID-19 pandemic on women in low-income and middle-income countries should adopt a systems thinking approach and be informed by the question of who is affected as opposed to who is infected. In adopting the systems thinking approach, responses will be more able to recognise and address the direct gendered effects of the pandemic and those that emerge indirectly through a combination of long-standing structural inequalities and gendered responses to the pandemic.


Subject(s)
COVID-19 , Humans , Pandemics , SARS-CoV-2 , Sustainable Development , Systems Analysis
2.
Bull World Health Organ ; 99(11): 783-794D, 2021 Nov 01.
Article in English | MEDLINE | ID: covidwho-1551419

ABSTRACT

Objective: To investigate vaccine hesitancy leading to underimmunization and a measles outbreak in Rwanda and to develop a conceptual, community-level model of behavioural factors. Methods: Local immunization systems in two Rwandan communities (one recently experienced a measles outbreak) were explored using systems thinking, human-centred design and behavioural frameworks. Data were collected between 2018 and 2020 from: discussions with 11 vaccination service providers (i.e. hospital and health centre staff); interviews with 161 children's caregivers at health centres; and nine validation interviews with health centre staff. Factors influencing vaccine hesitancy were categorized using the 3Cs framework: confidence, complacency and convenience. A conceptual model of vaccine hesitancy mechanisms with feedback loops was developed. Findings: A comparison of service providers' and caregivers' perspectives in both rural and peri-urban settings showed that similar factors strengthened vaccine uptake: (i) high trust in vaccines and service providers based on personal relationships with health centre staff; (ii) the connecting role of community health workers; and (iii) a strong sense of community. Factors identified as increasing vaccine hesitancy (e.g. service accessibility and inadequate follow-up) differed between service providers and caregivers and between settings. The conceptual model could be used to explain drivers of the recent measles outbreak and to guide interventions designed to increase vaccine uptake. Conclusion: The application of behavioural frameworks and systems thinking revealed vaccine hesitancy mechanisms in Rwandan communities that demonstrate the interrelationship between immunization services and caregivers' vaccination behaviour. Confidence-building social structures and context-dependent challenges that affect vaccine uptake were also identified.


Subject(s)
Patient Acceptance of Health Care , Vaccines , Child , Health Knowledge, Attitudes, Practice , Humans , Rwanda/epidemiology , Systems Analysis , Vaccination
4.
J Emerg Manag ; 19(7): 39-48, 2021.
Article in English | MEDLINE | ID: covidwho-1497651

ABSTRACT

The COVID-19 pandemic exposed numerous challenges in the emergency management (EM) response system. The article contends that had EM deliberately and systematically engaged in systems thinking; it would have been better able to anticipate and respond to many of the challenges. Reasons for EM not fully embracing systems thinking are discussed, including the perception that it is complex and theoretical. This article attempts to dispel these beliefs by first demonstrating how many systems-thinking concepts are already embedded in the EM ethos and then by illustrating the application of system principles in the context of the COVID-19 response. This article concludes by recommending EM invest in training to encourage the systematic application of system principles in emergency preparedness and response.


Subject(s)
COVID-19 , Civil Defense , Humans , Pandemics , SARS-CoV-2 , Systems Analysis
5.
J Emerg Manag ; 18(7): 209-223, 2021.
Article in English | MEDLINE | ID: covidwho-1497640

ABSTRACT

The emergence of COVID-19 in the United States has overwhelmed local hospitals, produced shortages in critical protective supplies for medical staff, and created backlogs in burials and cremations. Because systemic disruptions occur most acutely at a local scale, facilitating resource coordination across a broad region can assist local responses to COVID-19 surges. This article describes a structured systems approach for coordinating COVID-19 resource distribution across the six New England states of the United States. The framework combines modeling tools to anticipate resource shortages in medical supplies, personnel needs, and fatality management for individual states. The approach allows decision makers to understand the magnitude of local outbreaks and equitably allocate resources within a region based on the present and future needs. This model contributed to determining material distribution in New England as the 2020 COVID-19 surges unfolded in the spring and fall seasons. Using a systems analysis, the model demonstrates the translation of anticipated COVID-19 cases into resource demands to enable regional coordination of scarce resources.


Subject(s)
COVID-19 , Pandemics , Hospitals , Humans , Pandemics/prevention & control , SARS-CoV-2 , Systems Analysis , United States
6.
PLoS One ; 16(10): e0259037, 2021.
Article in English | MEDLINE | ID: covidwho-1496524

ABSTRACT

Epidemiological simulations as a method are used to better understand and predict the spreading of infectious diseases, for example of COVID-19. This paper presents an approach that combines a well-established approach from transportation modelling that uses person-centric data-driven human mobility modelling with a mechanistic infection model and a person-centric disease progression model. The model includes the consequences of different room sizes, air exchange rates, disease import, changed activity participation rates over time (coming from mobility data), masks, indoors vs. outdoors leisure activities, and of contact tracing. It is validated against the infection dynamics in Berlin (Germany). The model can be used to understand the contributions of different activity types to the infection dynamics over time. It predicts the effects of contact reductions, school closures/vacations, masks, or the effect of moving leisure activities from outdoors to indoors in fall, and is thus able to quantitatively predict the consequences of interventions. It is shown that these effects are best given as additive changes of the reproduction number R. The model also explains why contact reductions have decreasing marginal returns, i.e. the first 50% of contact reductions have considerably more effect than the second 50%. Our work shows that is is possible to build detailed epidemiological simulations from microscopic mobility models relatively quickly. They can be used to investigate mechanical aspects of the dynamics, such as the transmission from political decisions via human behavior to infections, consequences of different lockdown measures, or consequences of wearing masks in certain situations. The results can be used to inform political decisions.


Subject(s)
COVID-19/prevention & control , Communicable Disease Control/methods , Contact Tracing/methods , Berlin , COVID-19/metabolism , Cell Phone/trends , Computer Simulation , Germany , Hand Disinfection/trends , Humans , Masks/trends , Models, Theoretical , Physical Distancing , Population Dynamics/trends , SARS-CoV-2/pathogenicity , Systems Analysis
7.
PLoS Comput Biol ; 17(10): e1009360, 2021 10.
Article in English | MEDLINE | ID: covidwho-1496326

ABSTRACT

The spread of infectious diseases such as COVID-19 presents many challenges to healthcare systems and infrastructures across the world, exacerbating inequalities and leaving the world's most vulnerable populations most affected. Given their density and available infrastructure, refugee and internally displaced person (IDP) settlements can be particularly susceptible to disease spread. In this paper we present an agent-based modeling approach to simulating the spread of disease in refugee and IDP settlements under various non-pharmaceutical intervention strategies. The model, based on the June open-source framework, is informed by data on geography, demographics, comorbidities, physical infrastructure and other parameters obtained from real-world observations and previous literature. The development and testing of this approach focuses on the Cox's Bazar refugee settlement in Bangladesh, although our model is designed to be generalizable to other informal settings. Our findings suggest the encouraging self-isolation at home of mild to severe symptomatic patients, as opposed to the isolation of all positive cases in purpose-built isolation and treatment centers, does not increase the risk of secondary infection meaning the centers can be used to provide hospital support to the most intense cases of COVID-19. Secondly we find that mask wearing in all indoor communal areas can be effective at dampening viral spread, even with low mask efficacy and compliance rates. Finally, we model the effects of reopening learning centers in the settlement under various mitigation strategies. For example, a combination of mask wearing in the classroom, halving attendance regularity to enable physical distancing, and better ventilation can almost completely mitigate the increased risk of infection which keeping the learning centers open may cause. These modeling efforts are being incorporated into decision making processes to inform future planning, and further exercises should be carried out in similar geographies to help protect those most vulnerable.


Subject(s)
COVID-19/epidemiology , COVID-19/transmission , Epidemics , Refugees , SARS-CoV-2 , Bangladesh/epidemiology , COVID-19/prevention & control , Comorbidity , Computational Biology , Computer Simulation , Data Visualization , Disease Progression , Humans , Masks , Physical Distancing , Refugees/statistics & numerical data , Schools , Systems Analysis
8.
Int J Equity Health ; 20(1): 230, 2021 10 19.
Article in English | MEDLINE | ID: covidwho-1477426

ABSTRACT

BACKGROUND: Numerous reports have demonstrated the disproportionate impact that COVID-19 has had on vulnerable populations. Our purpose is to describe our health care system's response to this impact. METHODS: We convened a Workgroup with the goal to mitigate the impact of COVID-19 on the most medically vulnerable people in Springfield, Massachusetts, USA, particularly those with significant social needs. We did this through (1) identifying vulnerable patients in high-need geographic areas, (2) developing and implementing a needs assessment/outreach tool tailored to meet cultural, linguistic and religious backgrounds, (3) surveying pharmacies for access to medication delivery, (4) gathering information about sources of food delivery, groceries and/or prepared food, (5) gathering information about means of travel, and (6) assessing need for testing. We then combined these six elements into a patient-oriented branch and a community outreach/engagement branch. CONCLUSIONS: Our highly intentional and methodical approach to patient and community outreach with a strong geographic component has led to fruitful efforts in COVID-19 mitigation. Our patient-level outreach engages our health centers' clinical teams, particularly community health workers, and is providing the direct benefit of material and service resources for our at-risk patients and their families. Our community efforts leveraged existing relationships and created new partnerships that continue to inform us-healthcare entities, healthcare employees, and clinical teams-so that we can grow and learn in order to authentically build trust and engagement.


Subject(s)
COVID-19 , Community Health Workers , Delivery of Health Care , Humans , SARS-CoV-2 , Systems Analysis
9.
J Ambul Care Manage ; 44(4): 293-303, 2021.
Article in English | MEDLINE | ID: covidwho-1447660

ABSTRACT

COVID-19 necessitated significant care redesign, including new ambulatory workflows to handle surge volumes, protect patients and staff, and ensure timely reliable care. Opportunities also exist to harvest lessons from workflow innovations to benefit routine care. We describe a dedicated COVID-19 ambulatory unit for closing testing and follow-up loops characterized by standardized workflows and electronic communication, documentation, and order placement. More than 85% of follow-ups were completed within 24 hours, with no observed staff, nor patient infections associated with unit operations. Identified issues include role confusion, staffing and gatekeeping bottlenecks, and patient reluctance to visit in person or discuss concerns with phone screeners.


Subject(s)
Ambulatory Care Facilities/organization & administration , COVID-19/therapy , Continuity of Patient Care/organization & administration , Pneumonia, Viral/therapy , Respiratory Care Units/organization & administration , Adult , Aged , Boston/epidemiology , COVID-19/epidemiology , Female , Humans , Male , Middle Aged , Pneumonia, Viral/epidemiology , Pneumonia, Viral/virology , Referral and Consultation/statistics & numerical data , SARS-CoV-2 , Systems Analysis , Workflow
10.
Front Public Health ; 8: 585229, 2020.
Article in English | MEDLINE | ID: covidwho-1389250
11.
PLoS One ; 16(8): e0256363, 2021.
Article in English | MEDLINE | ID: covidwho-1362093

ABSTRACT

The most unexpected and toughest phenomenon that has occurred in recent times is the global COVID-19 pandemic. One of the first measures to prevent the spread of the disease was to close educational institutions. The students were forced to start a learning process through social networks and web platforms. In some countries, a return to face-to-face classes was established. However, weeks later, some of them had to return to virtual activities due to an upswing in the COVID-19 cases. In Mexico, classes have been held virtually, with face-to-face activities only re-established in two of the 32 states. In our state, Yucatan, scholarly activities are still virtual. In this work, the dispersion of COVID-19 at different academic establishments in Yucatan was simulated. Networks of Friendship, noncordial treatment, family ties and study groups were considered. Based on these networks, we evaluated the possibility of returning to school without inducing a rebound in the COVID-19 cases in the state. Agent-based simulations were used, with each student as an agent. Interaction rules were established based on international research regarding good practices in times of COVID-19. We used seven networks from different academic institutions, ranging from primary through college level. As a result, possible contagion curves were obtained for different scenarios, which leads to a discussion about the measures that would be relevant once a return to face-to-face classes is overseen. Simulations show that isolating students and reducing the number of students in the same classroom are good strategies and substantially reduce the possible contagiousness.


Subject(s)
COVID-19/epidemiology , Pandemics/prevention & control , Students, Medical/psychology , COVID-19/prevention & control , Humans , Mexico/epidemiology , Schools , Social Networking , Systems Analysis , Universities
12.
Int J Environ Res Public Health ; 18(15)2021 08 03.
Article in English | MEDLINE | ID: covidwho-1341675

ABSTRACT

Localized outbreaks of COVID-19 have been reported in sporting facilities. This study used the Agent-based Modeling (ABM) method to analyze the transmission rate of COVID-19 in different sporting models, sporting spaces per capita, and situations of gathering, which contributes to understanding how COVID-19 transmits in sports facilities. The simulation results show that the transmission rate of COVID-19 was higher under the Fixed Movement Route (FMR) than under the Unfixed Movement Route (UMR) in 10 different sporting spaces per capita (1, 2, 3, 4, 5, 6, 7, 8, 9, and 10 m2) (p = 0.000). For both FMR and UMR, the larger the sporting space per capita, the lower the virus transmission rate. Additionally, when the sporting space per capita increases from 4 m2 to 5 m2, the virus transmission rate decreases most significantly (p = 0.000). In the FMR model with a per capita sporting space of 5 m2, minimizing gathering (no more than three people) could significantly slow down the transmission rate of the COVID-19 virus (p < 0.05). This study concluded that: (1) The UMR model is suggested in training facilities or playing grounds; (2) The sporting space should be non-overcrowding, and it is recommended that the sporting space per capita in the sporting grounds should not be less than 5 m2; (3) It is important to maintain safe social distancing and minimize gathering (no more than three people) when exercising.


Subject(s)
COVID-19 , Computer Simulation , Humans , Physical Distancing , SARS-CoV-2 , Systems Analysis
13.
PLoS One ; 16(7): e0253579, 2021.
Article in English | MEDLINE | ID: covidwho-1329133

ABSTRACT

The entire world has suffered a lot since the outbreak of the novel coronavirus (COVID-19) in 2019, so simulation models of COVID-19 dynamics are urgently needed to understand and control the pandemic better. Meanwhile, emotional contagion, the spread of vigilance or panic, serves as a negative feedback to the epidemic, but few existing models take it into consideration. In this study, we proposed an innovative multi-layer hybrid modelling and simulation approach to simulate disease transmission and emotional contagion together. In each layer, we used a hybrid simulation method combining agent-based modelling (ABM) with system dynamics modelling (SDM), keeping spatial heterogeneity while reducing computation costs. We designed a new emotion dynamics model IWAN (indifferent, worried, afraid and numb) to simulate emotional contagion inside a community during an epidemic. Our model was well fit to the data of China, the UK and the US during the COVID-19 pandemic. If there weren't emotional contagion, our experiments showed that the confirmed cases would increase rapidly, for instance, the total confirmed cases during simulation in Guangzhou, China would grow from 334 to 2096, which increased by 528%. We compared the calibrated emotional contagion parameters of different countries and found that the suppression effect of emotional contagion in China is relatively more visible than that in the US and the UK. Due to the experiment results, the proposed multi-layer network model with hybrid simulation is valid and can be applied to the quantitative analysis of the epidemic trends and the suppression effect of emotional contagion in different countries. Our model can be modified for further research to study other social factors and intervention policies in the COVID-19 pandemic or future epidemics.


Subject(s)
Anxiety/prevention & control , COVID-19/psychology , Quarantine/psychology , COVID-19/epidemiology , COVID-19/transmission , Computer Simulation , Disease Outbreaks , Emotional Regulation , Emotions , Humans , Models, Statistical , Pandemics , Panic , SARS-CoV-2/isolation & purification , Systems Analysis
14.
PLoS Comput Biol ; 17(7): e1009149, 2021 07.
Article in English | MEDLINE | ID: covidwho-1325366

ABSTRACT

The COVID-19 pandemic has created an urgent need for models that can project epidemic trends, explore intervention scenarios, and estimate resource needs. Here we describe the methodology of Covasim (COVID-19 Agent-based Simulator), an open-source model developed to help address these questions. Covasim includes country-specific demographic information on age structure and population size; realistic transmission networks in different social layers, including households, schools, workplaces, long-term care facilities, and communities; age-specific disease outcomes; and intrahost viral dynamics, including viral-load-based transmissibility. Covasim also supports an extensive set of interventions, including non-pharmaceutical interventions, such as physical distancing and protective equipment; pharmaceutical interventions, including vaccination; and testing interventions, such as symptomatic and asymptomatic testing, isolation, contact tracing, and quarantine. These interventions can incorporate the effects of delays, loss-to-follow-up, micro-targeting, and other factors. Implemented in pure Python, Covasim has been designed with equal emphasis on performance, ease of use, and flexibility: realistic and highly customized scenarios can be run on a standard laptop in under a minute. In collaboration with local health agencies and policymakers, Covasim has already been applied to examine epidemic dynamics and inform policy decisions in more than a dozen countries in Africa, Asia-Pacific, Europe, and North America.


Subject(s)
COVID-19 , Models, Biological , SARS-CoV-2 , Systems Analysis , Basic Reproduction Number , COVID-19/etiology , COVID-19/prevention & control , COVID-19/transmission , COVID-19 Testing , COVID-19 Vaccines , Computational Biology , Computer Simulation , Contact Tracing , Disease Progression , Hand Disinfection , Host Microbial Interactions , Humans , Masks , Mathematical Concepts , Pandemics , Physical Distancing , Quarantine , Software
15.
PLoS Comput Biol ; 17(7): e1009146, 2021 07.
Article in English | MEDLINE | ID: covidwho-1305573

ABSTRACT

SARS-CoV-2 has spread across the world, causing high mortality and unprecedented restrictions on social and economic activity. Policymakers are assessing how best to navigate through the ongoing epidemic, with computational models being used to predict the spread of infection and assess the impact of public health measures. Here, we present OpenABM-Covid19: an agent-based simulation of the epidemic including detailed age-stratification and realistic social networks. By default the model is parameterised to UK demographics and calibrated to the UK epidemic, however, it can easily be re-parameterised for other countries. OpenABM-Covid19 can evaluate non-pharmaceutical interventions, including both manual and digital contact tracing, and vaccination programmes. It can simulate a population of 1 million people in seconds per day, allowing parameter sweeps and formal statistical model-based inference. The code is open-source and has been developed by teams both inside and outside academia, with an emphasis on formal testing, documentation, modularity and transparency. A key feature of OpenABM-Covid19 are its Python and R interfaces, which has allowed scientists and policymakers to simulate dynamic packages of interventions and help compare options to suppress the COVID-19 epidemic.


Subject(s)
COVID-19/prevention & control , Contact Tracing , Systems Analysis , COVID-19/epidemiology , COVID-19/transmission , COVID-19/virology , COVID-19 Testing , COVID-19 Vaccines/administration & dosage , Disease Outbreaks , Humans , Physical Distancing , Quarantine , SARS-CoV-2/isolation & purification
16.
Acad Med ; 96(7S): S6-S8, 2021 07 01.
Article in English | MEDLINE | ID: covidwho-1286597

ABSTRACT

The COVID-19 pandemic of 2020 exposed the reactive nature of the medical education community in response to a disruption that, at one time, may have seemed preposterous. In this article, the author reflected on the impact of an unpredictable plight on a system of medical education that (1) is continuous but doesn't function as a continuum and (2) requires adaptation but is steeped in a fixed mindset and structure that resists change. As a result, innovations which were previously considered impossible, such as time variable education and training, were forced into being. Inspired by the changes brought about by the pandemic, the ensuing decade is explored through a lens of possible futures to envision a path forward based on resilience rather than reactivity.


Subject(s)
COVID-19 , Competency-Based Education/organization & administration , Education, Medical/organization & administration , Models, Educational , Organizational Innovation , Competency-Based Education/methods , Creativity , Education, Medical/methods , Humans , Resilience, Psychological , Systems Analysis , United States
17.
Int J Environ Res Public Health ; 18(13)2021 06 22.
Article in English | MEDLINE | ID: covidwho-1282505

ABSTRACT

The COVID-19 pandemic has greatly influenced society in the past few years. Park accessibility and social distancing are considered important under the threat of a long-term epidemic. However, measures that can maintain park accessibility and diminish virus spreading synchronously have been seldom studied before, which may threaten public health in all major urban parks globally. This paper proposed a methodology based on an agent-based model to analyze capacities for parks by simulating park visitor behaviors when they all are social distancing. The model was derived from historical visitor data and realistic visitor behaviors in three park settings. Then, park capacities of varied contact conditions, different park policies, and layout adjustments were analyzed. First, congestions caused by social distancing without proper visitor control are found inside all parks. Second, 85 to 3972 square meters per person is predicted as a safe space in different parks. Third, the current results can be easily adjusted according to various concerns regarding infection distance and rate. Finally, it can be inferred that information provisions are more effective than space design adjustments and mandatory measures. The results can guide park managers and those who plan and design park settings. They are also helpful in improving knowledge of the mechanisms behind visitor behaviors. Moreover, these findings can be tested and verified in a variety of public spaces with many other contact-based illnesses.


Subject(s)
COVID-19 , Parks, Recreational , Humans , Pandemics , Physical Distancing , Recreation , SARS-CoV-2 , Systems Analysis
18.
Int J Mol Sci ; 22(10)2021 May 17.
Article in English | MEDLINE | ID: covidwho-1238898

ABSTRACT

Inflammation is a key mechanism for the clearance of infective agents and other inflammatory triggers and is pivotal for the repairing processes of the affected tissues. Inflammation is a multistep process driven by a great number of mediators which regulate specific aspects of the inflammatory response, in agreement with a well-defined chronobiological program. A great number of inflammation-related diseases show a deeply altered immune chronobiology (e.g., COVID-19-related cytokines storm). This aspect highlights the need for a deeper understanding of the inflammatory phenomenon. It is fundamental to study inflammation as a multilevel phenomenon. Of particular interest is the low-grade chronic inflammation, which is an etiological factor of many chronic diseases. Nowadays, the therapeutic approach to low grade chronic inflammation is one of the great challenges of traditional pharmacology. Currently, no drugs specifically designed for the treatment of chronic inflammatory forms are available. Today, bioregulatory systems medicine (BrSM) and low dose medicine (LDM), two pharmacological paradigms grounded in systems medicine, potentially represent new tools for the treatment of inflammation-related diseases. Scientific research has assessed the effectiveness and safety of both these therapeutic approaches, in particular for the management of chronic inflammatory conditions and chronic immunological dysregulations.


Subject(s)
Anti-Inflammatory Agents/pharmacology , COVID-19/metabolism , Cytokine Release Syndrome/metabolism , Cytokines/metabolism , Inflammation/metabolism , Systems Analysis , Acute Disease , Anti-Inflammatory Agents/therapeutic use , COVID-19/immunology , COVID-19/physiopathology , Chronic Disease/drug therapy , Humans , Inflammation/drug therapy , Inflammation/immunology , Inflammation/physiopathology
19.
Global Health ; 17(1): 59, 2021 05 21.
Article in English | MEDLINE | ID: covidwho-1238728

ABSTRACT

BACKGROUND: The COVID-19 pandemic is adversely impacting modern human civilization. A global view using a systems science approach is necessary to recognize the close interactions between health of animals, humans and the environment. DISCUSSION: A model is developed initially by describing five sequential or parallel steps on how a RNA virus emerged from animals and became a pandemic: 1. Origins in the animal kingdom; 2. Transmission to domesticated animals; 3. Inter-species transmission to humans; 4. Local epidemics; 5. Global spread towards a pandemic. The next stage identifies global level determinants from the physical environments, the biosphere and social environment that influence these steps to derive a generic conceptual model. It identifies that future pandemics are likely to emerge from ecological processes (climate change, loss of biodiversity), anthropogenic social processes (i.e. corporate interests, culture and globalization) and world population growth. Intervention would therefore require modifications or dampening these generators and prevent future periodic pandemics that would reverse human development. Addressing issues such as poorly planned urbanization, climate change and deforestation coincide with SDGs such as sustainable cities and communities (Goal 11), climate action (Goal 13) and preserving forests and other ecosystems (Goal 15). This will be an added justification to address them as global priorities. Some determinants in the model are poorly addressed by SDGs such as the case of population pressures, cultural factors, corporate interests and globalization. The overarching process of globalization will require modifications to the structures, processes and mechanisms of global governance. The defects in global governance are arguably due to historical reasons and the neo-liberal capitalist order. This became evident especially in the aftermath of the COVID-19 when the vaccination roll-out led to violations of universal values of equity and right to life by some of the powerful and affluent nations. A systems approach leads us to a model that shows the need to tackle several factors, some of which are not adequately addressed by SDGs and require restructuring of global governance and political economy.


Subject(s)
COVID-19/prevention & control , Global Health/trends , Systems Analysis , COVID-19/transmission , Humans , Pandemics/prevention & control , Pandemics/statistics & numerical data , Sustainable Development/trends
20.
BMJ ; 373: n1087, 2021 05 12.
Article in English | MEDLINE | ID: covidwho-1226751

ABSTRACT

OBJECTIVE: To estimate population health outcomes with delayed second dose versus standard schedule of SARS-CoV-2 mRNA vaccination. DESIGN: Simulation agent based modeling study. SETTING: Simulated population based on real world US county. PARTICIPANTS: The simulation included 100 000 agents, with a representative distribution of demographics and occupations. Networks of contacts were established to simulate potentially infectious interactions though occupation, household, and random interactions. INTERVENTIONS: Simulation of standard covid-19 vaccination versus delayed second dose vaccination prioritizing the first dose. The simulation runs were replicated 10 times. Sensitivity analyses included first dose vaccine efficacy of 50%, 60%, 70%, 80%, and 90% after day 12 post-vaccination; vaccination rate of 0.1%, 0.3%, and 1% of population per day; assuming the vaccine prevents only symptoms but not asymptomatic spread (that is, non-sterilizing vaccine); and an alternative vaccination strategy that implements delayed second dose for people under 65 years of age, but not until all those above this age have been vaccinated. MAIN OUTCOME MEASURES: Cumulative covid-19 mortality, cumulative SARS-CoV-2 infections, and cumulative hospital admissions due to covid-19 over 180 days. RESULTS: Over all simulation replications, the median cumulative mortality per 100 000 for standard dosing versus delayed second dose was 226 v 179, 233 v 207, and 235 v 236 for 90%, 80%, and 70% first dose efficacy, respectively. The delayed second dose strategy was optimal for vaccine efficacies at or above 80% and vaccination rates at or below 0.3% of the population per day, under both sterilizing and non-sterilizing vaccine assumptions, resulting in absolute cumulative mortality reductions between 26 and 47 per 100 000. The delayed second dose strategy for people under 65 performed consistently well under all vaccination rates tested. CONCLUSIONS: A delayed second dose vaccination strategy, at least for people aged under 65, could result in reduced cumulative mortality under certain conditions.


Subject(s)
COVID-19 Vaccines/administration & dosage , COVID-19/prevention & control , Public Health/statistics & numerical data , Time-to-Treatment/statistics & numerical data , Adult , COVID-19/diagnosis , COVID-19/epidemiology , COVID-19/virology , COVID-19 Vaccines/immunology , Hospitalization , Humans , Middle Aged , Occupations , Patient Simulation , SARS-CoV-2/genetics , SARS-CoV-2/immunology , Sensitivity and Specificity , Systems Analysis , Treatment Outcome , Vaccination
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