Key questions for modelling COVID-19 exit strategies

Combinations of intense non-pharmaceutical interventions ('lockdowns') were introduced in countries worldwide to reduce SARS-CoV-2 transmission. Many governments have begun to implement lockdown exit strategies that allow restrictions to be relaxed while attempting to control the risk of a surge in cases. Mathematical modelling has played a central role in guiding interventions, but the challenge of designing optimal exit strategies in the face of ongoing transmission is unprecedented. Here, we report discussions from the Isaac Newton Institute 'Models for an exit strategy' workshop (11-15 May 2020). A diverse community of modellers who are providing evidence to governments worldwide were asked to identify the main questions that, if answered, will allow for more accurate predictions of the effects of different exit strategies. Based on these questions, we propose a roadmap to facilitate the development of reliable models to guide exit strategies. The roadmap requires a global collaborative effort from the scientific community and policy-makers, and is made up of three parts: i) improve estimation of key epidemiological parameters; ii) understand sources of heterogeneity in populations; iii) focus on requirements for data collection, particularly in Low-to-Middle-Income countries. This will provide important information for planning exit strategies that balance socio-economic benefits with public health

Chelator Regulation of In Situ

A recently patented one-step in situ cross-linked alginate microencapsulation (CLAM) by spray-drying (i.e., the UC Davis CLAMs technology) can overcome the high cost of scale-up that limits commercial applications. While increasing calcium loading in the CLAMs process can increase the extent of cross-linking and improve retention and protection of the encapsulated cargo, the potential for residual undissolved calcium salt crystals in the final product can be a concern for some applications. Here, we demonstrate an alternate one-step spray-dry CLAMs process using pH-responsive chelation of calcium. The "Chelate CLAMs" process is an improvement over the patented process that controls ion availability based on pH-responsive solubility of the calcium salt. Hyaluronic acid was encapsulated in CLAMs to minimize swelling and release in aqueous formulations. CLAMs with 61% (d.b.) hyaluronic acid (HA-CLAMs) demonstrated restricted plumping, limited water absorption capacity, and reduced leaching, retaining up to 49% hyaluronic acid after 2 h in water. Alternatively, "Chelate HA-CLAMs" formed by the improved process exhibited nearly full retention of hyaluronic acid over 2 h in water and remained visibly insoluble after 1 year of storage in water at 4 °C. Successful hyaluronic acid retention in CLAMs is likely due in part to its ability to cross-link with calcium

Chelator Regulation of In Situ Calcium Availability to Enable Spray-Dry Microencapsulation in Cross-Linked Alginates.

A recently patented one-step in situ cross-linked alginate microencapsulation (CLAM) by spray-drying (i.e., the UC Davis CLAMs technology) can overcome the high cost of scale-up that limits commercial applications. While increasing calcium loading in the CLAMs process can increase the extent of cross-linking and improve retention and protection of the encapsulated cargo, the potential for residual undissolved calcium salt crystals in the final product can be a concern for some applications. Here, we demonstrate an alternate one-step spray-dry CLAMs process using pH-responsive chelation of calcium. The "Chelate CLAMs" process is an improvement over the patented process that controls ion availability based on pH-responsive solubility of the calcium salt. Hyaluronic acid was encapsulated in CLAMs to minimize swelling and release in aqueous formulations. CLAMs with 61% (d.b.) hyaluronic acid (HA-CLAMs) demonstrated restricted plumping, limited water absorption capacity, and reduced leaching, retaining up to 49% hyaluronic acid after 2 h in water. Alternatively, "Chelate HA-CLAMs" formed by the improved process exhibited nearly full retention of hyaluronic acid over 2 h in water and remained visibly insoluble after 1 year of storage in water at 4 °C. Successful hyaluronic acid retention in CLAMs is likely due in part to its ability to cross-link with calcium

How alginate properties influence in situ internal gelation in crosslinked alginate microcapsules (CLAMs) formed by spray drying.

Alginates gel rapidly under ambient conditions and have widely documented potential to form protective matrices for sensitive bioactive cargo. Most commonly, alginate gelation occurs via calcium mediated electrostatic crosslinks between the linear polyuronic acid polymers. A recent breakthrough to form crosslinked alginate microcapsules (CLAMs) by in situ gelation during spray drying ("CLAMs process") has demonstrated applications in protection and controlled delivery of bioactives in food, cosmetics, and agriculture. The extent of crosslinking of alginates in CLAMs impacts the effectiveness of its barrier properties. For example, higher crosslinking extents can improve oxidative stability and limit diffusion of the encapsulated cargo. Crosslinking in CLAMs can be controlled by varying the calcium to alginate ratio; however, the choice of alginates used in the process also influences the ultimate extent of crosslinking. To understand how to select alginates to target crosslinking in CLAMs, we examined the roles of alginate molecular properties. A surprise finding was the formation of alginic acid gelling in the CLAMs that is a consequence of simultaneous and rapid pH reduction and moisture removal that occurs during spray drying. Thus, spray dried CLAMs gelation is due to calcium crosslinking and alginic acid formation, and unlike external gelation methods, is insensitive to the molecular composition of the alginates. The 'extent of gelation' of spray dried CLAMs is influenced by the molecular weights of the alginates at saturating calcium concentrations. Alginate viscosity correlates with molecular weight; thus, viscosity is a convenient criterion for selecting commercial alginates to target gelation extent in CLAMs

How alginate properties influence in situ internal gelation in crosslinked alginate microcapsules (CLAMs) formed by spray drying.

Alginates gel rapidly under ambient conditions and have widely documented potential to form protective matrices for sensitive bioactive cargo. Most commonly, alginate gelation occurs via calcium mediated electrostatic crosslinks between the linear polyuronic acid polymers. A recent breakthrough to form crosslinked alginate microcapsules (CLAMs) by in situ gelation during spray drying ("CLAMs process") has demonstrated applications in protection and controlled delivery of bioactives in food, cosmetics, and agriculture. The extent of crosslinking of alginates in CLAMs impacts the effectiveness of its barrier properties. For example, higher crosslinking extents can improve oxidative stability and limit diffusion of the encapsulated cargo. Crosslinking in CLAMs can be controlled by varying the calcium to alginate ratio; however, the choice of alginates used in the process also influences the ultimate extent of crosslinking. To understand how to select alginates to target crosslinking in CLAMs, we examined the roles of alginate molecular properties. A surprise finding was the formation of alginic acid gelling in the CLAMs that is a consequence of simultaneous and rapid pH reduction and moisture removal that occurs during spray drying. Thus, spray dried CLAMs gelation is due to calcium crosslinking and alginic acid formation, and unlike external gelation methods, is insensitive to the molecular composition of the alginates. The 'extent of gelation' of spray dried CLAMs is influenced by the molecular weights of the alginates at saturating calcium concentrations. Alginate viscosity correlates with molecular weight; thus, viscosity is a convenient criterion for selecting commercial alginates to target gelation extent in CLAMs

Key questions for modelling COVID-19 exit strategies

Combinations of intense non-pharmaceutical interventions (lockdowns) were introduced worldwide to reduce SARS-CoV-2 transmission. Many governments have begun to implement exit strategies that relax restrictions while attempting to control the risk of a surge in cases. Mathematical modelling has played a central role in guiding interventions, but the challenge of designing optimal exit strategies in the face of ongoing transmission is unprecedented. Here, we report discussions from the Isaac Newton Institute 'Models for an exit strategy' workshop (11-15 May 2020). A diverse community of modellers who are providing evidence to governments worldwide were asked to identify the main questions that, if answered, would allow for more accurate predictions of the effects of different exit strategies. Based on these questions, we propose a roadmap to facilitate the development of reliable models to guide exit strategies. This roadmap requires a global collaborative effort from the scientific community and policymakers, and has three parts: (i) improve estimation of key epidemiological parameters; (ii) understand sources of heterogeneity in populations; and (iii) focus on requirements for data collection, particularly in low-to-middle-income countries. This will provide important information for planning exit strategies that balance socio-economic benefits with public health.</p

Key questions for modelling COVID-19 exit strategies

Combinations of intense non-pharmaceutical interventions (lockdowns) were introduced worldwide to reduce SARS-CoV-2 transmission. Many governments have begun to implement exit strategies that relax restrictions while attempting to control the risk of a surge in cases. Mathematical modelling has played a central role in guiding interventions, but the challenge of designing optimal exit strategies in the face of ongoing transmission is unprecedented. Here, we report discussions from the Isaac Newton Institute 'Models for an exit strategy' workshop (11-15 May 2020). A diverse community of modellers who are providing evidence to governments worldwide were asked to identify the main questions that, if answered, would allow for more accurate predictions of the effects of different exit strategies. Based on these questions, we propose a roadmap to facilitate the development of reliable models to guide exit strategies. This roadmap requires a global collaborative effort from the scientific community and policymakers, and has three parts: (i) improve estimation of key epidemiological parameters; (ii) understand sources of heterogeneity in populations; and (iii) focus on requirements for data collection, particularly in low-to-middle-income countries. This will provide important information for planning exit strategies that balance socio-economic benefits with public health

Agricultural landscape structure and invasive species : The cost-effective level of crop field clustering

Invasive pests in agricultural settings may have severe consequences for agricultural production, reducing yields and the value of crops. Once an invader population has established, controlling it tends to be very expensive. Therefore, when the potential impacts on production may be great, protection against initial establishment is often perceived to be the most cost-effective measure. Increasing attention in the ecological literature is being given to the possibility of curbing invasion processes by manipulating the field and cropping patterns in agricultural landscapes, so that they are less conducive to the spread of pests. However, the economic implications of such interventions have received far less attention. This paper uses a stochastic spatial model to identify the key processes that influence the vulnerability of a fragmented agricultural landscape to pests. We explore the interaction between the divergent forces of ecological invasion pressure and economic returns to scale, in relation to the level of clustering of crop fields. Results show that the most cost-effective distances between crop fields in terms of reducing food production impacts from an invasive pest are determined by a delicate balance of these two forces and depend on the values of the ecological and economic parameters involved. If agricultural productivity declines slowly with increasing distance between fields and the dispersal range of the potential invader is high, manipulation of cropping structure has the potential to protect against invasion outbreaks and the farmer can gain benefit overall from maintaining greater distances between fields of similar crops

Key questions for modelling COVID-19 exit strategies.

Combinations of intense non-pharmaceutical interventions (lockdowns) were introduced worldwide to reduce SARS-CoV-2 transmission. Many governments have begun to implement exit strategies that relax restrictions while attempting to control the risk of a surge in cases. Mathematical modelling has played a central role in guiding interventions, but the challenge of designing optimal exit strategies in the face of ongoing transmission is unprecedented. Here, we report discussions from the Isaac Newton Institute 'Models for an exit strategy' workshop (11-15 May 2020). A diverse community of modellers who are providing evidence to governments worldwide were asked to identify the main questions that, if answered, would allow for more accurate predictions of the effects of different exit strategies. Based on these questions, we propose a roadmap to facilitate the development of reliable models to guide exit strategies. This roadmap requires a global collaborative effort from the scientific community and policymakers, and has three parts: (i) improve estimation of key epidemiological parameters; (ii) understand sources of heterogeneity in populations; and (iii) focus on requirements for data collection, particularly in low-to-middle-income countries. This will provide important information for planning exit strategies that balance socio-economic benefits with public health

Key questions for modelling COVID-19 exit strategies

Combinations of intense non-pharmaceutical interventions (lockdowns) were introduced worldwide to reduce SARS-CoV-2 transmission. Many governments have begun to implement exit strategies that relax restrictions while attempting to control the risk of a surge in cases. Mathematical modelling has played a central role in guiding interventions, but the challenge of designing optimal exit strategies in the face of ongoing transmission is unprecedented. Here, we report discussions from the Isaac Newton Institute ‘Models for an exit strategy’ workshop (11–15 May 2020). A diverse community of modellers who are providing evidence to governments worldwide were asked to identify the main questions that, if answered, would allow for more accurate predictions of the effects of different exit strategies. Based on these questions, we propose a roadmap to facilitate the development of reliable models to guide exit strategies. This roadmap requires a global collaborative effort from the scientific community and policymakers, and has three parts: (i) improve estimation of key epidemiological parameters; (ii) understand sources of heterogeneity in populations; and (iii) focus on requirements for data collection, particularly in low-to-middle-income countries. This will provide important information for planning exit strategies that balance socio-economic benefits with public health