Improvements in childhood survival rates have been achieved in low- and middle- income countries that have made a commitment to improve access to cancer care. Accurate data on the costs of delivering cancer treatment in these settings will allow ministries of health and donors to accurately assess and plan for expansions of access to care. This study assessed the financial cost of treating two common pediatric cancers, nephroblastoma and Hodgkin lymphoma, at the Butaro Cancer Center of Excellence in rural Rwanda.A microcosting approach was used to calculate the per-patient cost for Hodgkin lymphoma and nephroblastoma diagnosis and treatment. Costs were analyzed retrospectively from the provider perspective for the 2014 fiscal year. The cost per patient was determined using an idealized patient receiving a full course of treatment, follow-up, and recommended social support in accordance with the national treatment protocol for each cancer.The cost for a full course of treatment, follow-up, and social support was determined to be between $1,490 and $2,093 for a patient with nephroblastoma and between $1,140 and $1,793 for a pediatric patient with Hodgkin lymphoma.Task shifting, reduced labor costs, and locally adapted protocols contributed to significantly lower costs than those seen in middle- or high-income countries. Research on the costs of pediatric cancer treatment in low-income countries can help inform policymakers and funders about the affordability of creating cancer treatment programs and provide information needed to advocate for greater investment in fighting this growing burden.More than 80% of the approximately 200,000 children diagnosed with cancer each year live in low- and middle-income countries (LMICs).This study assessed the financial cost of treating two common pediatric cancers, nephroblastoma and Hodgkin lymphoma (HL), at the Butaro Cancer Center of Excellence (BCCOE), located at the Butaro District Hospital in rural northern Rwanda. We hope these findings will strengthen the argument that pediatric cancers can and should be treated in LMICs and provide evidence to support greater resource allocation.4 Imaging and surgical services not currently available at BCCOE are provided through referral hospitals.The BCCOE is the referral center for cancer care for the country of Rwanda, offering preventive care, pathology-based diagnosis, staging, chemotherapy, referral for radiotherapy, follow-up, and palliative care, as well as psychosocial and practical support.2 Seven pediatric patients with HL (and approximately 23 adult patients) were diagnosed at BCCOE between July 2013 and June 2014. Pediatric patients were defined as patients ≤ 15 years of age at the time of diagnosis.Between July 2013 and June 2014, 35 patients with nephroblastoma, also known as Wilms tumor, were diagnosed; this represents the most common childhood malignancy seen at the BCCOE.A microcosting approach was used to calculate the per-patient cost for HL and nephroblastoma management. Costs were analyzed retrospectively from the provider perspective for the 2014 fiscal year . The provider perspective reflects costs incurred by the entities responsible for implementing the cancer care program. Our focus was on capturing the costs of implementing an effective cancer program and did not include patient costs, such as the out-of-pocket expenses of patients or the larger societal costs of treatment, such as lost productivity. Nor did it try to estimate what insurance coverage might be, because the national health care insurance in Rwanda does not currently cover cancer care.The cost per patient was determined using an idealized patient receiving a full course of treatment, follow-up, and recommended social support in accordance with the national treatment protocol. The microcosting methodology was selected to allow for ministries of health and providers to better plan for the implementation of cancer programs. The sensitivity analysis demonstrates that these calculations are likely to give accurate estimates. All costs paid in Rwandan francs were converted to US dollars ($) using the conversion rate at the time of purchase, where available, and the median 2014 exchange rate of 674 Rwandan francs to 1US$ when a daily rate was not available.An annualized total for fixed start-up costs, equipment, and supplies for the cancer center was calculated, and a proportion was assigned based on the total number of patients with cancer. All annual overhead costs for the oncology program  were assigned to each patient with cancer treated on the basis of patient volume and time on the ward. During the study period, most chemotherapy was administered as an in-patient treatment. Time on the ward was calculated assuming a total of 40 days for HL and 52 days for nephroblastoma, including both treatment and follow-up. The estimates are consistent with the average hospitalization time for a full course of treatment and one adverse event.2 and weight of 15 kg. Chemotherapy costs for HL were calculated assuming a child with stage III HL, a body surface area of 1 m2 and a weight of 30 kg. Drug prices were calculated based on prices paid by the Partners in Health procurement team at the time of treatment and vial usage. The Partners in Health procurement team is able to negotiate prices across their delivery sites, resulting in economies of scale. Oncology drugs are exempt from taxation in the country. On the basis of vial usage, the methodology accounts for drug waste and leads to results that are both more accurate and more conservative.All chemotherapy and supportive care drugs were enumerated following the established treatment protocol for each disease in Rwanda. Chemotherapy costs for nephroblastoma were calculated assuming a child with metastatic disease stage and a body surface area of 0.6 m5 was used to determine the full cost of appropriate CT scans and surgery per patient with nephroblastoma. CT scans are currently not part of the protocol for pediatric HL and were therefore not included.Computed tomography (CT) scans and surgery were conducted off site at a referral hospital in Kigali. The 2012 Rwandan National Reference for Rates and Hospital CentresThe majority of pathology costs are incorporated in labor and overhead calculations. Additional costs for the program included items such as shipment of samples to Boston, training and travel costs for pathology laboratory technicians, customs and duty charges for reagents, and consumables related to the pathology laboratory. The average cost per patient for these expenses was allocated on the basis of all new diagnoses at BCCOE during the study period.Radiotherapy is not available in Rwanda; patients needing this treatment must be referred out of the country. Radiotherapy is used in limited situations where its inclusion in the treatment plan is deemed as essential for cure. The average cost of radiotherapy per patient was adjusted to reflect the low volume of patients receiving this treatment for nephroblastoma. If residual disease exists after chemotherapy, in rare cases, a patient with HL can be sent for radiotherapy. Given the rarity of this occurrence, this cost was not included in our analysis.All blood products are provided free of charge to hospitals through the National Center for Blood Transfusion Division of the Rwanda Biomedical Center. The cost given by the National Center for Blood Transfusion for each RBC unit is $88. Provider interviews were used to determine an average use of 5 RBC units per patient with nephroblastoma and 7 RBC units per patient with HL over the treatment cycle.BCCOE is located in a remote district of Rwanda 3 hours from the capital, and funding for transportation is provided to each patient in need to ensure that patients can access treatment. The median round trip cost of transportation was combined with the average number of trips for a full course of treatment and follow-up to determine the full cost of supporting transportation for treatment per patient.We identified all relevant hospital staff involved in the treatment of pediatric patients with cancer, including doctors, nurses, social workers, cashiers, laboratory technicians, intake coordinators, and pharmacy staff. We then interviewed physicians, nurses, technicians, and administrative staff to determine the major activities performed in treating each type of cancer and created process maps to estimate the amount of time each type of provider spent on each activity with each patient. We adjusted staff salaries by the estimated total number of paid hours worked each year to determine a cost per hour for each provider. The provider cost per hour was allocated to the relevant patient care activities to create a total staff cost per patient. The analysis assumes one adverse event per patient on the basis of provider interviews of the typical experience and treatment decisions made for these specific cancers. Given the short duration of treatment, we did not apply a discount rate. We conducted a one-way sensitivity analysis to determine the parameters most likely to affect the cost per patient.The total cost of management for a patient with metastatic nephroblastoma was $2,093 . Labor aAll qualifying patients in need receive transportation support to ensure that they are able to reach treatment. As a result, transportation costs represent a significant proportion of the total cost for the provider (14%); however, it is important to note this is based on the assumption that a patient will require support for every trip during a full course of treatment and follow-up. Radiotherapy represents only 6% of the total cost because of the small proportion of patients receiving this treatment option. Capital costs, overhead, and supportive care medications are all minimal costs at the patient level.We conducted a one-way sensitivity analysis to determine how changes in our assumptions might affect the analysis and to identify the parameters most likely to affect the cost per patient . We vari6 , the adjusted average cost was $1,490 per patient. The cost of $2,093 represents the idealized cost of treating a patient with nephroblastoma, whereas $1,490 was the per-patient cost adjusted for expected survival and loss to follow-up outcomes at BCCOE.The current cost per patient diagnosed with nephroblastoma is based on a patient with metastasis completing a full cycle of treatment and follow-up. Of course, not all patients will present at the same stage, have the same disease progression, or complete treatment and/or follow-up. If one assumes that outcomes will continue to be similar to the initial outcomes seen in Rwanda for patients with Wilms tumor treated at BCCOEThe total cost for a full course of treatment, follow-up, and recommended social support for a patient with HL is estimated to be $1,793 . Blood p7 the total cost of treatment adjusted for expected survival and loss to follow-up was estimated to be $1,140 per patient, representing a reduction of $652 per patient.Assuming we can expect similar completion rates to continue at BCCOE (including 68% of patients completing both treatment and follow-up),8 Accurate assessments of the costs for low-income countries can help both donors and governments make informed investment decisions with regard to cancer treatment facilities. These assessments can affect political will to dedicate resources, even when costs are high relative to other potential investments.9The cost for a full course of treatment and follow-up was determined to be between $1,490 and $2,093 for a patient with nephroblastoma and between $1,140 and $1,793 for a pediatric patient with HL. The cost of pediatric cancer treatment in Rwanda is significantly lower than that seen in high-income countries, often estimated to be between $40,000 and $100,000, depending on cancer type.6 Given the different methodologies and the low number of patients in each study, the consistent results between the two studies helps to bolster the case for the accuracy of these costs. A study conducted in two South African hospitals found that the total cost of diagnosing, staging, and treating a child with HL was $6,647.10 Our analysis found a much lower cost per patient. CT scans and radiotherapy were included as standard components of management in the South African study. This accounted for a significant difference in cost because radiotherapy and CT scans were not standard components of care in the Rwandan analysis. However, if CT scans were more widely available and radiotherapy could be provided in the country, they could become standard components of care at BCCOE as well.A study conducted in the Kigali University Teaching Hospital in Rwanda found that treatment costs for nephroblastoma were consistent with the findings of this study, with costs between $1,831 for early disease and $2,418 for advanced disease.9 Improving cost transparency would also help with negotiations to adjust costs appropriately for different settings.Drug prices also reflect a large portion of the difference; in Rwanda, the course of chemotherapy is approximately one fifth of the cost outlined in the South African study. Despite the lower cost of chemotherapy in Rwanda and the use of generic drugs, chemotherapy still represents a significant cost. As cancer treatment becomes more widely available, collective bargaining could be leveraged to further reduce costs. The example of HIV/AIDS medications is particularly instructive, because concerted advocacy efforts and bulk pricing reduced medication costs in low-income countries by as much as 90% from the price when first introduced in high-income countries.11 Rwanda uses a task-shifting model to allow generalists  to provide care with structured support from volunteer US-based oncologists, further reducing costs.2 Locally adapted protocols that minimize toxicity and length of stay in the hospital (and are therefore less expensive) have been shown to cure a significant number of children when applied with appropriate social support in low-resource settings.13A number of factors contribute to the ability of BCCOE to provide quality and effective cancer care at lower costs. As with many developing countries, the cost of labor for the cancer center is significantly less expensive than in more economically developed countries. Labor costs for the entire cancer center  is less than the average annual salary of $246,526 for one oncologist in the United States.The analysis is limited in that the cost per patient was determined using an idealized patient receiving a full course of treatment and follow-up, in accordance with the current Rwandan protocol for treatment of each cancer. Often, the complexity, toxicity, and length of treatment combined with the availability of resources can profoundly affect the cost of care stemming from these protocols. Protocols may be further adapted to the local context over time. As the recommended protocols are further refined, we can expect to see corresponding changes in the cost of treatment. In addition, limitations of the program include a high volume of patients for limited bed space and staff time. As more hospital beds and paid staff are made available, the cost per patient may increase as each patient receives a greater share of available resources.A number of data points were restricted or unavailable. The estimates of the costs of CT scans and surgery in our analysis are based on the prices charged by the relevant referral hospitals. We did not have access to the data necessary to perform a full and accurate accounting of the costs of these procedures on the basis of actual resource consumption. Because a relatively small percentage of patients receive these services, this cost analysis has limited sensitivity (4%). However, a more accurate cost of these procedures would further refine our estimates. Labor costs produced from provider interviews are subject to recall bias. Multiple providers’ opinions were sought to minimize this bias as much as possible. In addition, the BCCOE relied on volunteer labor, including volunteer doctors, nurses, and pathologists. The cost per patient assumes all providers are paid staff and does not take into account free labor. Therefore, this methodology likely overstates the true cost per patient.The one-way sensitivity analysis  revealed14 The cost of treatment provides a strong call to action for the global health community to support the establishment of new cancer programs, particularly considering that the long-term survival rates for children with cancer in high-income countries exceed 80%. Innovative approaches, such as those used at BCCOE, which combine a strong commitment to cancer care, adaptation of protocols to the local setting, task shifting, and collaborative partnerships, have great potential to produce affordable, quality cancer care. This study demonstrates that an investment of less than $2,100 per patient can save children’s lives and protect families from the hardship and heartache of losing a child to cancer.In conclusion, the majority of new pediatric cancers are now occurring in LMICs, and these countries are often the least equipped to respond to the growing burden.


The methodology is applied to over 1600 signatories in Europe, representing over 80 million inhabitants. Results show that, in general, signatories are reducing both types of emissions. However, there are also cases where emissions increase. We explore the reasons behind these changes and highlight the role of technological improvement. This work calls for an increased coherence between climate and air quality plans at the local scale and provides a first step and a tool to support signatories, even the smallest ones, to move in this direction.The Covenant of Mayors (CoM) is a successful European initiative which encourages local authorities to be proactive in fighting climate change. Recently, it expanded to cover adaptation and energy access/poverty and became a global initiative. In this study we investigate an additional perspective: synergies and trade-offs between climate and air quality. Signatories pledge to reduce their Greenhouse gas (GHG) emissions and voluntarily report their emissions, energy consumption and the measures that they carry out to reach their goals. We develop a methodology to estimate air pollutant emissions corresponding to CO In Auguby 2020) . The actTrade-offs and co-benefits between climate change and air pollution are well known . They haA first step to support local authorities in this aspect is to try and extract information from the data they already submit to the CoM. This was done, for the first time, in our previous work  where we2 emissions, in baseline and monitoring reports, the corresponding emissions of air pollutants. These reports show a ‘snapshot’ of the signatories’ final energy use in two different years, but they are not directly linked to the measures put in place. Therefore, even though we cannot consider single actions using these data, it is possible to evaluate the change in the time interval between baseline and monitoring years. The estimate of air pollutant emissions is obtained by combining CoM data with data obtained from air pollutant emission scenarios or inventories, such as the Greenhouse Gas - Air Pollution Interations and Synergies (GAINS) model  model  and the S) model . The imp2 and/or air pollutant emissions have increased and trade-offs. Results show that reported increase of biomass burning for residential heating, often considered neutral in terms of CO2 emissions, can have a large impact on the emissions of air pollutants. On the contrary, the role of technological improvement is shown to be particularly important to limit PM2.5 emissions in the transport sector despite the increases in consumption (in particular for diesel cars).The methodology is applied to over 1600 selected signatories showing that, in most cases, they are reducing both types of emissions. However, it is also possible to identify cases where COFinally, this analysis shows that there is the potential to integrate air quality aspects in the CoM, which could guarantee consistency between air quality and climate policies at local scale.22 emissions for different sectors and fuels (referred to as energy carriers). The actions, implemented and planned to achieve the emission reduction targets, are also reported (note that signatory cities pledge actions to support the implementation of the 40 % greenhouse gas-reduction target by 2030). To monitor the evolution of emission reductions the signatories submit also a Monitoring Emission Inventory (MEI), where they summarise, in the same format as the BEI, the energy consumption and the CO2 emissions for the monitoring year. BEI, MEI and actions are described by each signatory in a Sustainable Energy and Climate Action Plan (SECAP). The changes in energy consumption (by sector carrier) between BEI and MEI is what we use in this work.Signatories submit a Baseline Emission Inventory (BEI), for a baseline year of their choice, summarising energy consumption and COactivity levels  and the corresponding emissions of air pollutants (e.g. kton of NOx) per sector (e.g. passenger cars), activity (e.g. gasoline) per country and per different scenarios starting from 1990 to 2030 with 5 years intervals. The ratio between emissions and activities is referred to as implied emission factor, which we note as p, sub-sector s, carrier c and year y, in kton/PJ for example).In addition to the CoM data, we use the GAINS model. GAINS  is a toosectors (e.g. public transport) and carriers (e.g. diesel fuel) as defined by the CoM inventories, to the sectors (e.g. buses) and activities (e.g. medium distillates), as defined by the GAINS model (or EDGAR). It is therefore possible to associate different (implied) emission factors to the CoM sectors and carriers (and reporting year) and estimate the emissions of air pollutants corresponding to the reported energy consumption. The results of the present study rely on the matching of the 2.1•2 direct and indirect emissions (due to the consumption of grid-supplied electricity) come from final energy consumption in residential, commercial and institutional buildings and facilities. Emissions from industrial buildings and facilities, agriculture/forestry/fisheries, and from ‘energy generation’ industries are not accounted for in our analysis. Note that heat and cold supplied by district heating/cooling networks are not included.macro-sector RES  corresponds to ‘Stationary Energy/Buildings’: CO•2 emissions (direct emission from fuel combustion and indirect emission due to consumption of grid-supplied energy) occurring for road transport within the local authority boundary are reported. Emissions, disaggregated into municipal, public, private and commercial transport, are accounted for in our analysis within the Transport macro-sector.macro-sector TRA corresponds to ‘Transportation’: all COThe CoM data used in the current paper are reported by the signatories in the CoM platform. The reported data must reflect accurately the content of the official SECAP document that each signatory submits. We provide here a brief description of the activity data and emissions reported in the platform and used in the present analysis. We are considering data referring to the residential (RES) and transport (TRA) macro-sectors.2 nor air pollutants, related to heat and cold supplied by district heating/cooling networks . For district heating reporting is not mandatory and therefore data are sparse. The available data-set does not allow us to consistently infer local emissions of air pollutants as we do not know with which technologies and fuels heat and cold are produced. The same problem arises for electricity consumption, but whereas heat and cold are generally produced locally, electricity generation is generally not located within the city boundaries and supplied by the grid. For electricity therefore we do consider CO2 emissions (as reported by the signatories) but, as we cannot infer local emissions of air pollutants from a possible local contribution, these pollutant emissions cannot be accounted for at the moment.It should be noted that in the RES sector we are not taking into account emissions, neither CO2 emissions reported by the signatories are calculated through default emission factors as described by COAnother important point to underline is that the results presented in this analysis, in terms of BEI and MEI activity and emissions data, are aggregated to the macro-sector level, whereas in the baseline and progress reports data is allocated in the due sub-sector . Therefore, in this study, whenever there is a reference to the transport or the residential macro-sectors it is always implied that the reference is to the sectors and carriers explicitly reported by the city within that macro-sector (and not the complete macro-sector).2 emission inventories a series of checks is developed to identify and remove the errors. These checks are part of the validation procedure that the Joint Research Centre (JRC) performs on the data, subsequently providing to the cities. JRC has observed that these feedback cycles improve the quality of data reported over time. That is particularly important in this analysis, as we are considering the effect of progress reported in the emission inventories.Furthermore, experience has shown that not all the data collected on the CoM platform can be considered complete and reliable. This is because of the voluntary nature of the initiative, the difficulty of adapting sometimes local specificities to the CoM reporting framework, and the occurrence of inputting errors. For these reasons, in order to build a robust and reliable sample of CODetails on this validation procedure and further checks that are carried out specifically for this work are described in the Supplementary Information (SI).Finally, the analysis concerns 1653 signatories whose inventories were selected in terms of quality and completeness, out of the 1845 signatories of the initial data-set. As shown in As said earlier, signatories are free to chose their reporting years, which are summarised in 2.2The estimate of air pollutant emission factors is based on the detailed matching between CoM sectors and carriers to the corresponding GAINS ones. Details of the matching, the GAINS scenario considered, and corresponding calculations of emission factors (depending on the country and year) are reported in the SI.The main simplifying assumptions underlying these estimates are that the national emission factors are assumed representative of the local ones in each city and that emission factors vary linearly within 5 years intervals (as this is the data available from GAINS). The first assumption is a very uncertain and simplifying one, that does not allow to evaluate measures specifically affecting the emission factors at the local level. In these cases only the effects due to the variation of activity can be accounted for. Examples of measures that can affect the emission factors are: a specific type of new natural gas bus substituting part of the public transport fleet, specific systems for biomass use in the residential sector, etc. The difference between national average and local emission factors can be especially significant for larger cities that may implement additional regulations with respect to the national ones, as for example a low emission zone (banning older and most polluting vehicles from a certain area) or a ban on the burning of wood or other fuels. The analysis could therefore be greatly improved by the integration of local data. Larger cities in particular may have more detailed information about their locally relevant emission factors. Most of the signatories are however represented by small to medium size cities, as shown in With Technological Improvement. A second set considers a hypothetical world without technological improvement, that is to say both BEI and MEI use the same emission factors corresponding to the year of the BEI . In this case, the changes in fuel mix and consumption levels are considered but not the evolution of the technologies. This set is referred to as Without Technological Improvement. CO2 emission factors are taken as reported by the cities in the CoM for both the BEI and the MEI. This implies that ‘Technological Improvement’ refers only to local emissions of air pollutants and not to CO2 emissions.In the analysis two sets of air pollutant emission factors are used. A first set considers emission factors for the BEI and the MEI corresponding to their respective years. The evolution of emission factors through the years is taken into account and this set is referred to as In the SI the description of the methodology using EDGAR   and (macro) sector , are summarised in As described in Section 2 emission changes per person per year, are reported in Overall results for the corresponding CO2 and air pollutant emissions.In the following paragraphs, results are further elaborated. In order to better understand trade-offs and co-benefits between CO42 emissions versus the ones estimated in this study in terms of air pollutant emissions. This allows to clearly trace the progress of each signatory and identify trade-offs and co-benefits. 2 emissions) in the case without technological improvement. For the residential sector the effect is not that pronounced and the corresponding analysis is presented in the SI. Furthermore it should be noted that, for representation purposes, the axis are limited and not all data-points are represented. Outliers are, in particular, very high percentage changes of PM2.5 emissions per person in the residential sector (see SI). These changes usually correspond to very low emission levels in the BEI, which increase considerably, for example, because of the rise of biomass burning, in the MEI. It should be underlined that emission factors for biomass burning are extremely uncertain.It is interesting to present results in terms of relative changes per person between the MEI and BEI years, directly showing what signatories report in terms of COTo better show the changes between the two panels, Analysing •2 and air pollutants between the BEI and the MEI and therefore co-benefits between air quality and climate change. Measures that bring cities to this quadrant are the ones that lead to reduction of activity  as well as the ones that lead to a reduction of emission factors  but only when associated with a reduction of activity. Energy efficiency measures applied in the context of the CoM are analysed in detail in Most results are in the 3rd quadrant (bottom-left), showing both reduction of emissions of CO•2 emissions and an increase of air pollutant emissions. Most of the points in this quadrant correspond to PM2.5 emissions in the residential sector.The 4th quadrant (bottom-right) represents the trade-off between a decrease of CO•2 emissions. This is mainly due to increased activities which can, in certain cases, be compensated by a reduction of air pollutant emission factors due to technological improvement.The 1st (top-right) and 2nd quadrants (top-left) have the smallest number of points. The 1st quadrant represents a detrimental effect for both types of emissions that can be attributed to increased activities. The 2nd quadrant represents a reduction of air pollutant emissions despite an increase of COStarting from the case ‘With Technological Improvement’:•2 are unchanged). This shows the importance of the technological improvement.As expected, results are shifted to the right, with more emissions of air pollutants  and energy use change per person and per fuel (see the SI for the complete list of acronyms). For most cities in this quadrant CO2 emission changes are due to reduced fuel use , heating oil (HO), diesel (MD)) along with an increase of the use of biomass (BIO) (see top and bottom panels). The middle panel shows that, in absolute terms, BIO contributes to the largest increases in PM2.5 emissions.It is interesting to analyse more in detail the 4th quadrant where, as shown in 2, but it can have a very large impact on air pollutant emissions (this may be the reason for the outliers mentioned above). Furthermore, as underlined earlier, we do not know which biomass technologies the city implemented, therefore, at this stage we have to rely on national average emission factors.A note of caution: with the data available we cannot know if, for example, some cities decided to report biomass use with greater detail in the MEI with respect to the BEI. For example, sometimes, the reported energy use for biomass in the BEI can be zero or close to zero, whereas it increases by many folds in the MEI. For biomass, this has little impacts on CO4.22 emissions.Another interesting quadrant is the 2nd one  available data, already considering real driving emissions). Without technological improvement there would have been an increase of PM2.5 emissions and a higher increase in NOx emissions. The decrease in NOx emissions associated to GSL is due both to the decrease in activity level and the technological improvement.5The methodology developed in this study allows to link climate mitigation to air quality, consistently and considering local data. This link is rarely considered at the local scale, which means that data for validation of our approach are scarce and patchy. In any case, we performed a first attempt to crosscheck our approach, comparing results for single cities to the air pollutant emissions that the cities report elsewhere . Preliminary results can be found in the SI.The approach also has some limitations, already highlighted in the text or in the relevant sections in the SI but that the authors find useful to also underline and summarise here. (i) The main one is that, at this stage, we only use national emission factors. We cannot therefore take into account a local technology mix which may be different from the national one (e.g. the specific composition of the vehicle fleet in terms of Euro-standards in a city). (ii) One should also keep in mind that the CoM is not designed to tackle air quality in the first place, and any estimate of air pollutant emissions is only a rough approximation which is not meant to substitute a detailed air quality plan. As a consequence we cannot account for all local emissions of air pollutants, as for example air pollutant emissions due to local energy generation . District heating networks, in particular, should be evaluated in more detail. For example, trade-offs between climate and air quality can arise when the heat source is switched from large industries and power plants outside the city to smaller biomass fueled installations in or near the city itself. (iii) Furthermore, it should be underlined that the approach, given the data available, does not consider single measures but rather the ‘bundle of measures’ implemented by signatories together with the effect of national policies. It is therefore not possible to ascribe the changes in emissions of air pollutants entirely to the CoM initiative. (iv) Finally and obviously, the quality of results strongly depends on the quality and detail of the input data submitted by the signatories (see SI for details on data-cleaning).•2 emissions between baseline and monitoring years.The approach allows to clearly identify trade-offs and co-benefits obtained by signatories in terms of air pollutant emissions and CO•Technological improvement has been of fundamental importance to limit the increase of air pollutant emissions despite increases in consumption patterns. This is especially true for PM2.5 emissions in the transport sector (in particular for diesel cars).•Most of the changes reported by the cities correspond to co-benefits for both climate change mitigation and air quality related emission reductions.•2 and increasing PM2.5 emissions).It is possible to clearly identify trade-offs between air quality and climate, as for example due to the use of biomass in the residential sector  and to allow signatories to evaluate themselves the impact of single actions and measures . Finally the aim of this work, beyond the analysis presented in this paper, would be to allow cities themselves to evaluate the impact on air quality of their local climate mitigation measures, to limit possible trade-offs between these two objectives.6https://github.com/esperluette/airpollutants_script_for_com.The code, in the R language , developEmanuela Peduzzi: Conceptualization, Methodology, Investigation, Formal analysis, Data curation, Validation, Visualization, Writing - review & editing, Supervision. Marta Giulia Bald: Data curation, Methodology. Enrico Pisoni: Conceptualization, Methodology, Writing - review & editing. Albana Kona: Data curation, Methodology. Paolo Bertoldi: Data curation, Writing - review & editing. Fabio Monforti-Ferrario: Methodology, Writing - review & editing, Project administration.The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.


This perspective piece describes how policymakers should consider inequalities as potential long-term consequences of the current coronavirus epidemic. In addition to health and economic costs, governments and the international community should consider the repercussions of their mitigation and suppression measures, as they might deepen inequalities between the developing and developed world, poor and rich within societies, women and men, and vulnerable populations. This is a call to action for more coordinated efforts at the international level that does not turn a blind eye on this aspect of the pandemic.The developed world is facing an unprecedented epidemic of a novel pathogen, COVID-19. Worldwide more than 1.4 million confirmed cases and 83 000 deaths have been recorded, as of April 8, 2020 [Governments around the world are acting to reduce the reproduction number R0 (the average number of new infections caused by each infected person) below one and flatten the curve of the contagion. Mitigation and suppression measures include: closing borders, closing schools, case isolation of symptomatic individuals and their contacts, social distancing, and widescale lockdowns of populations . By obseCountries in the developing world have already experienced and survived other crises, which deteriorated their economies. Among others, West Africa and the DRC were hit by Ebola in 2014-2016 and 2018-2020, respectively. Mozambique was affected by Cyclone Idai in 2019, and billions of desert locusts swarmed Somalia, Ethiopia, and Kenya earlier this year. Conflicts, such as the recent Rohingya crisis in Northern Myanmar, forced the displacement of millions of people. However, nothing seems to be on the scale of what is expected for COVID-19 , which iSince poorer economies have limited financial resources and weaker health systems, with insufficient health workforce and testing capacity, leaders are acting quickly to try to save lives. Yet, the economic consequences of these measures might devastate their economies even further. Take India for example, where still 60% of the population lives below the World Bank’s median poverty line. The shutdown order sparked mass migration of workers who were forced to walk hundreds of miles to their home villages after public transport was suspended. In Kenya, where President Kenyatta ordered milder measures to slow the coronavirus outbreak, informal laborers, who account for more than 80% percent of the total workforce, are left without jobs. More generally, in developing countries most of the communities do not have access to clean water, let alone soap. Additionally, as individuals mostly rely on their daily income to put food on the table, they are facing the hard choice to either go to work with a chance of getting the virus or assured starvation if they stay at home. There is a concrete risk that people will die of hunger before the curve will flatten .Among the consequences of the coronavirus outbreak in developing economies, something else to consider is how the epidemic could ramp up inequality. First, poorer countries are likely to be hit harder than rich countries, due to poor infrastructure and lack of resources which will hamper public health efforts. This will widen inequality between the developed and developing world. Second, both in the developed and developing world, inequality in the societies are expected to widen as well. Poorer workers relying on daily income will be the most affected as they are at a greater risk of losing their jobs. Another inequality that is expected to increase relates to gender. As 70% of women are health workers and women do more than three-quarters of all unpaid care work , women wAfter the Ebola outbreak in West Africa, one of biggest epidemics to occur in recent history, the international community was criticized for its failure to warn the world in time and for the slow and inadequate response . The WorAs a result, international agencies are now considering acting for developing countries in other ways. The World Bank Group just approved a US$ 1.9 billion fast-track package to strengthen the COVID-19 response in the developing world and shorten the time to recovery . EconomiThere is still an urgent need for action to help mitigating the impact of the coronavirus epidemic in less developed countries. As those economies with few recorded cases are already feeling the consequences of the contagion, this is a call to coordinated efforts at the international level. The response should reach those most vulnerable not only to mitigate the health and economic costs of the virus, but more importantly to limit the widening of inequality worldwide.


The novel coronavirus SARS-CoV-2 emerged from a zoonotic transmission in China towards the end of 2019, rapidly leading to a global pandemic on a scale not seen for a century. In order to cast fresh light on the spread of the virus and on the effectiveness of the containment measures adopted globally, we used 26,869 SARS-CoV-2 genomes to build a phylogeny with 20,247 mutation events and adopted a phylogeographic approach. We confirmed that the phylogeny pinpoints China as the origin of the pandemic with major founders worldwide, mainly during January 2020. However, a single specific East Asian founder underwent massive radiation in Europe and became the main actor of the subsequent spread worldwide during March 2020. This lineage accounts for the great majority of cases detected globally and even spread back to the source in East Asia. Despite an East Asian source, therefore, the global pandemic was mainly fueled by its expansion across and out of Europe. It seems likely that travel bans established throughout the world in the second half of March helped to decrease the number of intercontinental exchanges, particularly from mainland China, but were less effective between Europe and North America where exchanges in both directions are visible up to April, long after bans were imposed. Towards the end of 2019, a novel virus jumped species from an unidentified host to humans, associated with an outbreak of pneumonia ,4, a knoSARS-CoV-2 causes severe acute respiratory disease in humans, known as coronavirus disease 2019 (COVID-19), which may also include gastrointestinal and neurological symptoms ,12,13,14Traditional evolutionary approaches have been applied to study the phylogeny of SARS-CoV-2. These are, in particular, maintained and updated on the GISAID website . HoweverThe first study  was undeA more recent study  applies Here, we analyzed almost an order of magnitude more sequences than this most recent study and applied novel methodologies to establish a more confident identification of the root. Like the previous studies referred to above, we co-opted approaches from human intraspecific phylogeography, as applied in the past, especially to mitochondrial DNA. In particular, we used the reduced-median (RM) network algorithm  to generIn our study, we highlighted a major feature of the spread of the virus to which phylogeographic analysis was uniquely suited and to which the study of mitochondrial genomes has made important contributions in the past. This is the extent and impact of founder effects on the dispersal of the virus around the human populations of the world. Furthermore, highlighting intercontinental dispersals of the various virus lineages allowed us to comment on the effectiveness of the early travel restrictions implemented by some countries.We collected SARS-CoV-2 complete genomes from the GISAID website  on 14 MaWe aligned sequences using the MAFFT version 7 online . The begWe used the reduced-median algorithm , implemeFollowing some exploratory analysis, we chose to reconstruct the primary architecture of the global phylogenetic network of SARS-CoV-2 variation by using only haplotypes that were present at absolute frequency higher than 10 in the database. We used the three outgroup sequences to root the tree by including them in the network analysis. These specified well-defined clades and excluded the possibility of inferring artefactual branches generated by low-quality sequences. As this reconstruction proved stable even after adding the low-frequency haplotypes, and since various conflicting nomenclatures have been proposed, none of which has been grounded in a reliable rooting of the tree, we used this network to create a new working nomenclature for the phylogeny. For this, we used letter labels established by GISAID/nextstrain (A and B) intercalated with numbers  and letters  as in the cladistic system established for human mitochondrial DNA . FollowiWe discounted the possibility that recombination might adversely affect the analysis. In a highly variable genome, recombination generates distinctive patterns in phylogenetic networks, which we did not observe. Instructively, it has been erroneously claimed several times for human mtDNA ,32, but Recombination has usually been proposed to have affected the virus genome before the jump to humans, perhaps between bat and pangolin viruses ,35, whicWe colored the networks according to both the geography of the sample (place of collection) for the phylogeographic analysis and date of collection for a chronological analysis. We identified hypothetical founders between the major continents in the networks: Africa, Oceania , East Asia (mainly China), South Asia, Southwest Asia, Europe, South America, and North America. We considered South Asia and Southwest Asia separately from East Asia for the founder analysis, as the history of these region in terms of SARS-CoV-2 spread seems to derive more directly from Europe than to the ultimate East Asian source region.For the analyses of intercontinental founders, we considered as candidate founders only those that resulted in at least two samples in the sink continent. By excluding singletons, we confirmed that the founders were haplotypes established within the sink population with at least one hypothetical epidemiological link . We analyzed all of the networks phylogeographically and considered all hypothetical intercontinental founders (as direct matches or inferred matches) ,37. To eA limitation of the analyses concerned the presence of frequent haplotypes spread across several continents . In sucFollowing the application of quality control criteria on the obtained dataset , we obtaThe defined root lay midway between the short branch separating the two major clades, A and B. It was separated by a single variant (a transition at nucleotide position 8782) from the reference sequence, defining clade A, and a second variant (a transition at nucleotide position 28144), defining clade B . Both clThe network suggested a second possible root due to a reticulation involving one of these two positions . The altWe used this network to establish the working cladistic nomenclature shown in We show the phylogenies for all the clades in the tree in Haplogroup B showed less global spread than its sister clade A. It emerged in China, where the earlier cases were detected and already displayed great diversity in terms of derived branches  before sClade A also had a likely origin in mainland China, as was the case for haplogroup B. Not only were early cases detected but substantial diversity was already present . This diWe established the cumulative distribution of the number of founders in each continent/region according to the source of each founder. Again, we focused on the numbers of founders and not their impact (frequency) in the sink population. While the phylogeographic signal could be captured well with even a low sample size, the frequency depended much more on the number of sequences carried out for each country . The resThe graphics show that, from the end of February and early March, Europe was the source for the vast majority of new founder sequences detected globally  with fouFollowing this steep increase in the number of founders during March, the plots begin to level off during April, suggesting that intercontinental transmissions were being brought under control, and most subsequent transmissions occurred through local transmission and evolution of clades already present.COVID-19, the disease caused by coronavirus SARS-CoV-2, was not the first coronavirus infection to jump species into humans in the last 20 years , but it Here, we extended the initial work of Forster et al.  and GómeThis was most likely horseshoe bats ,44, as fMuch of the ensuing analysis depends on correctly locating the root of the phylogeny. The root we identified differed substantially from those detected by both Forster et al.  and GómeWe conclude that we have an accurate and rather comprehensive sketch of the first six months of the evolution and dispersal of the virus, with the caveat that sampling was not carried out evenly around the world, up until mid-May 2020. We largely restricted our inferences to intercontinental rather than intracontinental dispersal of the virus, in order not to be misled by sampling biases from one country to another. In particular, the majority of European samples were from the United Kingdom, with countries such as Italy—which was at the root of the European outbreak—poorly represented. It is also true that there was considerable sampling bias from one continent to another, with Europe and North America much more heavily represented than Asia, Oceania, or Africa. However to some extent this also reflected the severity of the pandemic in these regions during the period in question, and the sheer scale of the present dataset means that even the less well-represented continents have a large number of samples.The strong phylogeographic patterns in the data and their concordance with the time of sampling suggest that the global patterns were well-represented in our networks. For example, despite relatively few samples from China, they were concentrated both in the earliest phases of the outbreak (December 2019 to January 2020) and close to (and either side of) the root of the network, and few of the expansion lineages seen in other continents have been sampled in China. In contrast to van Dorp et al. concluding that “Everything is everywhere”   C,D. StriThese results were consistent with the very early dates for the first cases in Europe—in Germany, Italy and France—dating to the end of January 2020, in comparison with other continents, and even other parts of Asia outside China. There were few founders originating in China, and of these just one (A1a) underwent a massive expansion in Europe and beyond. Whilst the source of COVID-19 was clearly in China, the spread of the global pandemic during the first six months was largely fueled by the expansion in Europe.Why this particular subclade underwent such a huge expansion is not obvious. The single mutation defining subclade A1a is a transition in the RNA polymerase gene and it is not clear that this would be likely to provide the virus with enhanced infectivity. Gómez-Carballa et al.  found feA potential implication of this analysis concerns our understanding of the effectiveness of the various travel bans issued in different countries towards the reduction of intercontinental transmissions. Early studies suggested that travel restriction had limited impact on the spread of the pandemic ,52. The On 11 March 2020, the US extended travel restrictions to foreign nationals who had visited the EU Schengen Area countries within the previous two weeks, with the UK and Ireland being included five days later and a recommendation against non-essential travel for US citizens from 19 March 2020. Clearly, the number of founders from Europe did decrease after that period. We considered an average incubation period of around five days to account for the possibility that some founders might be detected later by chance. This showed a total of 16 founders detected in the month after 11 March, against 46 in the month before (about a third). It is clear, however, that the travel ban on foreign nationals, but not on US citizens, did not stop the entrance of new founders in the US. Furthermore, new founders were detected in April, suggesting that the measures did slow down the spread but remained less than fully effective in stopping it.The pattern was similar with Australia. Australia initially showed the highest number of founders of any country . However, with the establishment of strict controls on the entry of foreign nationals on 20 March and a two-week quarantine instituted from 28 March, new founders fell drastically from 65 in the month before to 13 in the month following (down to a fifth). This was at a time when Australia was headed towards winter, which might be thought to exacerbate the spread of the virus. Although the measure was not fully effective, it seems to have been more so than in the US. In fact, travelling from China had been previously banned from 1st February and only one founder was detected in Australia on the 21st February from a possible East Asian source.Much more dramatic results were evident for East Asia. China established much stricter travel restrictions on entry to virtually all foreign nationals by 27 March. By 1st April, most East Asian countries had implemented strict travel restrictions. The data suggest that the arrival of new founders ceased entirely before the end of March. However, when the measures were effective overall, it was difficult to disentangle the effects of travel restrictions from those of very strict lockdowns.For Africa, South America, South Asia, and Southwestern Asia, the data are much less robust. For all regions, it seems that strict travel restrictions may have substantially reduced the number of founders, although they did not prevent them altogether. For example, India introduced travel bans by 18th March and the number of founders in the month before and after corresponded to 10 and 3, respectively. Once again, however, it is difficult to disentangle the positive results from the effect of other measures, since Europe, the region that was largely seeding the pandemic through March and early April, was almost entirely under lockdown from the second half of March.For Europe, although the EU restricted the arrival of non-EU nationals after 17th March, the border-free Schengen Area between most EU countries remained open. Travel restrictions within the continent were introduced by some countries to a variable extent at varying times, with various piecemeal attempts to implement self-quarantine regimes. For example, the UK quarantine measures and travel restrictions were only brought in in June 2020. Climate may also have been a confounding factor and it is not entirely clear how the number of founders correlates with the spread of the pandemic.However, by March, the virus was already widespread throughout Europe, which had become the epicenter of the pandemic. Most of the evolution of SARS-CoV-2 in Europe was the result of local spread within the continent, reflecting the fact that the borders that remained open across most of Europe. Even so, by the end of March and in April, new founders were still being detected (14 founders), all from a North American source, suggesting that even intercontinental travel restrictions were less effective between Europe and the US. Given the massive proliferation that had taken place within Europe, any such permeability remained a potential risk for other parts of the world.We demonstrated here that the phylogeographic detection and analysis of founder lineages can be a powerful approach with which to track intercontinental movements of a fast-spreading pathogen in fine detail. Not only that, but it has practical value in allowing us to evaluate the impact of travel restrictions imposed at various times around the world. We highlighted how some were more effective than others in slowing down the spread, but also by unequivocally demonstrating that none were wholly effective in halting the spread. Air travel has clearly been a major driver of the pandemic, and our analysis suggests that stricter travel restrictions appear to be more effective in slowing the spread. Insights from evolutionary analysis can therefore also serve as a learning experience to help manage current and future threats to public health.


The world is witnessing an alarming rate of displacement and migration, with more than 70.8 million forcibly displaced individuals, including 26 million refugees. These populations are known to have increased vulnerability and susceptibility to mental and physical health problems due to the migration journey. Access of these individuals to health services, whether during their trajectory of displacement or in refugee-hosting countries, remains limited and challenging due to multiple factors, including language and cultural barriers and unavailability of the refugees’ health records. Cloud-based electronic health records (EHRs) are considered among the top five health technologies integrated in humanitarian crisis preparedness and response during times of conflict. This viewpoint describes the design and implementation of a scalable and innovative cloud-based EHR named Sijilli, which targets refugees in low-resource settings. This paper discusses this solution compared with other similar practices, shedding light on its potential for scalability. The number of forcibly displaced individuals, including refugees, has reached an alarming rate globally, with 70.8 million forcibly displaced individuals, including around 26 million refugees , of whomRefugees are often exposed to stressful conditions of vulnerability, poverty, poor nutrition, and marginalization prior to and during the journey of migration, a situation that increases their susceptibility of developing different health problems, including mental health problems -9. From The growing and continuous influx of refugees imposes challenges on the health systems of the refugee-hosting countries vis-à-vis catering to the needs of these populations and providing essential health services , especiaElectronic health records (EHRs) have been progressively adopted in resource-constrained settings  and confEHRs have evolved in the past decade  and haveA relatively recent type of EHRs is the cloud-based EHR system . Cloud-bA few types of EHRs have been implemented for migrants and refugees  and haveSimilarly, the Refugee Assistance Information System (RAIS) is an EHR system developed by the United Nations High Commissioner for Refugees (UNHCR) to track, monitor, and provide assistance to refugees registered with UNHCR ,31. It cLebanon, one of the main LMICs housing refugees, hosts around 1 million registered Syrian refugees in addition to more than 400,000 unregistered refugees , renderiRegarding the use of eHealth systems for refugees in Lebanon, both UNRWA’s eHealth system and the RAIS are applicable in the country, yet the use of both systems remains bounded by the aforementioned restrictions.Another example of existing technologies in Lebanon is Phoenix. Phoenix is an EHR system developed by the Lebanese Ministry of Public Health (MoPH), and it functions exclusively among the 229 primary health care centers (PHCs) that operate under the supervision of the MoPH. Phoenix EHR targets disadvantaged Lebanese and refugees from different nationalities who receive primary health care within the national network of PHCs governed by the MoPH. It contains vital patient information, including documentation, guidelines, orders, and results . The sysThe pressing need for innovative digital solutions that would enhance refugees’ access to needed health services in low-resource settings, regardless of their migration journey, triggered the development of Sijilli (meaning “my record” in Arabic).This paper describes the design of the cloud-based mobile EHR system and reports on its implementation among Syrian refugees in Lebanon. Sijilli  was launSijilli is designed to allow interaction and to support convenient workflows among different users, from the data entry personnel to the administrators and ultimately to the end users, namely health providers and refugees.Data entry personnel collect the health information from refugees in different remote and underserved areas using data entry–friendly software run on tablet computers. Worth mentioning is that the use of the Sijilli software system by data entry personnel does not require internet connectivity and is done completely offline. The system adopts a simple user interface design to accommodate users and data collectors of diverse health backgrounds. Once the health information of the refugee is entered into the system, the Sijilli data collection software generates a password-protected and advanced encrypted standard (AES) PDF document of the health record of the refugee. The password of the PDF is generated exclusively and blindly  for the Sijilli holder and consists of the first letters of the refugee’s first name, father’s name, mother’s name, and family name, in addition to the 4 numbers of their year of birth, entered in this specific order. This simple composition of the password allows Sijilli holders to recall their passwords by following simple instructions. The Sijilli health record in its PDF version is then downloaded on a key-shaped flash drive  and handWorth noting is that patients cannot alter any data contained in their Sijilli records, neither through the PDF on the flash drive nor through the patient’s portal on the Sijilli website. On the other hand, health providers can have access to refugee patients’ Sijilli records when provided with the personal identification number (PIN) and the security questions that are recognized exclusively by Sijilli holders/refugees. External health providers can see all the health data of the refugee, originally collected by the data entry personnel at the time of the creation of the health record, and can also add clinical notes online at the time of encounter with the patient using the cloud-based version of the Sijilli EHR. No modifications to the original patient information can be made by the health providers. This ensures traceability and protects the liability of the GHI and Epic team.The Sijilli EHR is composed of 7 sections covering sociodemographic information, social and lifestyle habits, medical and surgical history, obstetrics and gynecological (OB/GYN) conditions for women only, medication use, vaccination history, and mental health screening. The data entered in the sociodemographic section allow the creation of the password and security questions used at times of access to the health record.The sociodemographic section includes questions on basic sociodemographic information, such as the previous occupation in the country of origin where conflict is taking place and the current occupation in the refugee-hosting country, which allows the identification of potential occupational health hazards and risk factors. Other information collected includes the location of the settlement and the year of migration, among other information. The section also includes questions that may affect the exposure of the refugee to health risks, including parental consanguinity, given that consanguineous marriage is a deeply rooted social practice among the Syrian refugee population. Knowledge about parental consanguinity enables the health care provider to explore and identify genetic disorders such as thalassemia. Allergies are also entered in this section to indicate any source of allergy that the refugee has.Further risk factors can be identified through data entered into the social and lifestyle section, which namely addresses smoking, alcohol drinking, and physical exercise. As the Syrian refugee crisis shifts from an acute emergency to a protracted crisis, NCDs and preventative medicine become a vital aspect of the health care response to refugee populations.The medical and surgical history section was designed to allow the selection of one or multiple medical conditions or surgical procedures, if any, using a drop-down menu that includes the most common conditions and surgeries, derived from the International Classification of Diseases, 10th Revision developed by the World Health Organization . DiseaseWith regards to the OB/GYN section, it is worth noting that this section was not originally embedded in the system, given that OB/GYN-related conditions were included in the general medical and surgical history section. However, a stand-alone OB/GYN section was added during the project implementation phase to take into consideration that the majority of the refugees having their Sijilli records created were women of child-bearing age, many of whom were pregnant. Moreover, a high pregnancy complication rate was noted by the women, which required the addition of a section dedicated to OB/GYN that included pregnancy-related complications to ensure proper and comprehensive documentation. The aforementioned section includes questions on gravida, para, aborta, method of delivery and associated complications, breastfeeding practice, and use of contraception.Davis’s Drug Guide for Nurses, which classifies medications according to their type  [To record any medications that the refugee is taking, a section on medication use is included in the Sijilli software system. Medications included cover mainly those taken for chronic conditions, in a drop-down menu format. Categorization of medications was based on gs, etc) . The datThe vaccination history section was included due to the outbreak of communicable diseases among the refugee population, such as the repetitive measles outbreaks witnessed among the refugee population in Lebanon. This section includes all required vaccines by the Lebanese MoPH. It is also designed to allow data entry personnel to indicate if school vaccines were given in Syria, given that this was generally a routine practice.The record then navigates to the mental health screening section, which uses the Patient Health Questionnaire-9 (PHQ-9). It is well established that refugees are at an increased risk of posttraumatic stress disorder, major depressive disorder (MDD), generalized anxiety disorder, and other behavioral and emotional problems. We elected to screen for MDD in particular, as previous research has shown that it is the most common and debilitating condition among Syrian refugees in Lebanon . The PHQ. In parallel, refugees who are Sijilli holders can also access their respective record through the password-protected PDF version of the EHR or through the portal on the Sijilli website by providing their PIN and answering security questions about their record.The Sijilli EHR system was designed to give different levels of access authorization to different users, such as data collectors and data entry personnel, administrators, external health providers, and refugees. Data entry personnel are on the front lines collecting information from the refugee population in areas often lacking network connectivity. All data from the data entry hardware  hosting the Sijilli data collection software can be wiped out after being synced back to the hub. The administrators, on the other hand, can access the Sijilli administrator web application, which is not available outside the internal network. The application can be used to authenticate hardware used for data collection and data entry, process synced requests, and update code sets that can be used in the Sijilli data collection software. Administrators can also generate a deidentified report of the health records for research purposes. The administrator web-based application can only be used by users authenticated in the AUB network and authorized by administrators through the web application. External health providers can access a specific refugee’s Sijilli EHR by providing a PIN and answering security questions, which are only recognized by the refugee, examine a summary of the refugee patient’s Sijilli EHR, and add clinical notes for future care sought by the refugeeGiven that Sijilli is a cloud-based EHR, data security is of particular concern and has been considered by addressing several key points. These include access to data, which is driven by role-based user access whereby once the data get into the database, only external health providers and the refugees can access patient records by providing the PIN and answering specific security questions. The access of administrators is restricted to deidentified personal health information of the refugees following data upload to the Sijilli database. In terms of authentication, hardware used by data entry personnel are independently authenticated by the administrator. In cases where laptops are used for data collection and data entry, the disk on the Sijilli data collection application is encrypted to protect against theft. Data are then wiped out after being uploaded to the Sijilli hub database. The PDF files generated in the Sijilli data collection application are password protected with a refugee-friendly PIN and AES encryption. For access through the Sijilli portal, external health providers and refugees can only access one Sijilli record at a time, and a captcha check has been added to the external web applications to prevent robots from accessing multiple records. All data in motion were set to be network protected using transport layer security 1.2. An audit trail exists in the hub database to indicate the access patterns to the health records by external health providers.Sijilli is characterized by 3 independent server applications that are cloud enabled and can be independently scaled up based on load and usage patterns. The Sijilli data collection application can be installed on as many laptops or tablets as required for data collection/data entry, and the syncing of data occurs when the laptops or tablets used are within the internal network.Administrators can manage the code sets and other metadata associated with the Sijilli application from the administrator application. This metadata can be synced to all the Sijilli data collection applications when the data from the data collector application are downloaded to the Sijilli hub. In terms of maintainability, the server teams have the authority to install the updates to the applications independently of each other.A key feature of the Sijilli EHR is its contextualized design. The design of each of the Sijilli data collection applications, the EHR itself, and the Sijilli website portals was tailored to the needs and interest of each of the multiple users/stakeholders involved.First, the design of the Sijilli data collection application used for primary creation of the Sijilli EHR for refugees was based on the input of several health providers, including physicians, nurses, community health workers, medical residents, and medical students. This was done to ensure that the platform developed is user-friendly at the time of Sijilli EHR creation and time efficient in terms of data entry and collection. The Sijilli data collection application then underwent beta testing on a sample of 100 refugees, after which the application underwent some calibration and fine-tuning steps. These mainly included changes in the units of categories used, the addition of some medical conditions to the drop-down menu, and the addition of a complete section on OB/GYN conditions for female refugees. Health providers were also involved in the design of the Sijilli website, the portal through which they can update the cloud-based EHR of refugees visiting a health facility. This is to ensure that the website/platform is user-friendly and smooth to use. The platform includes the Arabic translation of instructions to accommodate non–English-speaking health providers, who are common in the Syrian-Lebanese context.Migrating populations and refugees continue to face obstacles in accessing health care services  and expePrevious studies have examined the association between EHR adoption and improvement in the quality and continuity of health care in refugee settings and have emphasized the importance of the adoption of these innovative technologies for the great promise they hold in such resource-constrained settings ,30,43-46The previously described UNRWA’s eHealth system  and the In terms of inclusiveness, the UNRWA’s eHealth system is designed to target Palestinian refugees that are registered with the UNRWA, and it is only functional through the health centers in the 5 fields of UNRWA’s operations . LikewisWith the impending challenge of refugee migration, initially to neighboring host LMICs, followed by opportunistic migration to European and possibly North American countries, the importance of an innovative, universally accessible, and digital technology becomes more emphasized . AccordiSijilli’s potential for scalability and interoperability lies in the fact that Sijilli is a low-cost cloud-based EHR that can be easily exported to conflict-affected or crisis-affected areas that lack the required digital infrastructure, and, more importantly, it omits the need for physically held patient records. Furthermore, such solutions can be transported with the migrating user across several host settings with guaranteed security that puts the refugee and the host service provider at ease. Countries with fragmented health care systems would also benefit from a parallel solution, which would allow service providers to exchange and consolidate the patient’s health-related information and interventions in one comprehensive, secure, and easy-to-access EHR.In conclusion, the Sijilli EHR represents a model for an innovative and scalable cloud-based solution that could be replicated for several vulnerable populations in different low-resource or crisis settings. Sijilli EHR's contextualized design, architecture with multilayered security, and process design and implementation highlight the potential applicability of this digital health solution to different populations and settings, with specific considerations for cases of different contexts and users. Sijilli EHR has a crucial role in enhancing refugees’ access to health services throughout the displacement and migration journey.


Attention is a central component of cognitive and behavioral processes and plays a key role in basic and higher-level functioning. Posner’s model of attention describes three components or networks of attention: the alerting, which involves high intensity states of arousal; the orienting, which involves the selective direction of attention; and the executive control, which involves cognitive functions such as conflict resolution and working memory. The Attention Network Test (ANT) is a computerized testing measure that was developed to measure these three networks of attention. This project describes the ANT, its widely used variants, and the recently developed ANT Database, a repository of data extracted from all studies that have used the ANT as of 2019. To illustrate the potential uses of the database, two meta-analyses conducted using the ANT Database are described. One explores task performance in children with and without attention deficit/hyperactivity disorder (ADHD). The other one explores regional differences between studies conducted in China, Europe, and the United States. We are currently in the process of integrating the database into a publicly available web interface. When that work is complete, researchers, clinicians, and the general public will be able to use the database to explore topics of interest related to attention. The development and maintenance of attentional capacity is central to cognitive performance. Attentional functioning plays a crucial role in task performance in the daily facets of life, and impairments in attention are present in a multitude of psychiatric disorders such as Alzheimer’s, Parkinson’s, stroke, and schizophrenia . In a seThe Attention Network Test (ANT) is a tool developed in 2002 by One component of attention is the alerting network, which corresponds to the achievement and maintenance of an alert and vigilant state. Activation in the right frontal and parietal hemispheres in the brain occurs when completing tasks that involve the alerting network . In the Orienting is the ability to selectively attend to a sensory pathway. Overt orienting involves sensory–motor engagement to stimuli, such as the redirection of head and eye movements . Covert Executive control is a term that encompasses many functions, such as problem solving, decision making, self-regulation, and conflict resolution. The ANT targets the latter of these by measuring the participant’s ability to ignore distractor stimuli. This component of attention presents with activation in the anterior cingulate gyrus and dorsolateral prefrontal cortex . NetworkFollowing the development of the ANT, a number of variants of the task emerged. The Attention Network Test for Interactions (ANT-I) introduced an auditory stimulus  to generate alerting and made the peripheral cue uninformative. The implementation of the auditory cue was designed to allow exploration of the interaction between the alerting and orienting networks . The useA multitude of other variations to the ANT have been developed in subsequent years. The L-ANT or Lateralized ANT was first developed in 2008 by In our initial exploration (in 2016) of the impact and prevalence of the ANT, over 2,000 articles were identified that had cited the seminal Fan et al. paper. We then sought to explore how many participants had participated in experiments using this testing measure or one of its variants to explore the growing interest in the use of this tool . This prNotably, at its current iteration, the database has been collated from over 3,000 studies that have cited the seminal ANT paper. The purpose of this paper is to describe this database and to illustrate its usefulness with some examples. It is our plan to make the database available to researchers, clinicians, and the general public via a web-based interface, the development of which is underway. This resource has allowed us to conduct two meta-analyses to date: explorations of attentional performance in children with and without attention deficit/hyperactivity disorder (ADHD), and regional differences in attentional processing between participants residing in China, Europe, and the United States. As previously described in The ANT Database was generated using the PubMed, Google Scholar, and Web of Science search engines with a comprehensive search of articles that had cited the original http://attentionnetwork.ca/.Data extraction was completed manually, and information pertaining to the purpose of the study, participant demographics, condition or clinical subset, number of participants in each condition, geographical region, and version of the ANT were entered into a spreadsheet. Error rates, mean RTs, and corresponding standard deviations/errors were extracted when provided. RTs and standard deviations/errors were extracted from the results section, supplementary tables, and, if not provided in the text, data figures using the WebPlotDigitizer, a web-based extraction tool . To dateA meta-analysis was performed on studies having conducted research with a clinical population of children with a diagnosis of ADHD and matched neurotypical healthy controls. Children with ADHD present with symptoms of consistent challenges with sustained attention, hyperactive behavioral tendencies, and challenges in organization and short-term memory consolidation.Despite the concerns of increased rates of ADHD that have been brought forth, the prevalence of children who meet diagnostic criteria has been shown to be relatively consistent over the past three decades across major geographical regions . HoweverImpairments in executive functioning have been proposed to be associated with ADHD over the past three decades . ChildreThis meta-analysis consisted of response time data (accuracy data were reported by too few studies) from studies that had both a control and an ADHD group, with participants in both groups ranging from 6 to 13 years of age. One study, Mean age weighted by the number of participants in a study was calculated for the ADHD group (10.8 ± 1.58 years) and the control group (10.6 ± 1.53 years). Forest plots for each study in this meta-analysis are presented in The hierarchical model also permits quantification of heterogeneity between studies for each measure, reflecting how much the studies differ from one to another over and above mere measurement error. Such differences would be attributable to unmodeled differences between the studies’ respective methods  or sample populations . Accounting for this heterogeneity is one of the primary benefits of the hierarchical model employed here, and this modeling choice is validated to the degree that the posterior distribution on the heterogeneity parameter is shifted away from zero. The findings from our ADHD meta-analyses are consistent with Using the ANT-I , In structural MRI studies, brain regions associated with the alerting and executive networks have been shown to be different in individuals with ADHD . The orbDifferences in linguistics and parental interactions have been shown to exist across cultures. The orienting network develops as a function of socialization within culture and community. Executive functioning, which involves the voluntary facilitation of attention, has apparent connections to an individual’s cultural environments . Given tThis meta-analysis explored cross-cultural differences in the three networks of attention. Regions in which the studies were conducted were identified through the methods section of each paper. Studies that had used the ANT were then grouped together by region and matched by age and number of participants. This resulted in 27 studies in total and nine from each region . Each region had a combined number of 330 ± 5 participants. A detailed breakdown of the demographics and sources for this meta-analysis is presented in Mean age, weighted by the number of participants in a study for China (37.2 ± 8.57), Europe (33.9 ± 7.55), and the United States (32 ± 9.4), was similar across all three regions. Forest plots for each study in the cross-cultural meta-analysis are presented in As in the previous application, quantitative inference was achieved through a Bayesian hierarchical model, coded and sampled using Stan . Each coThe posterior distributions for each measure and region are shown in The differences in the cross-cultural exploration have intriguing epistemological implications and suggest regional variations in attentional processing. Consistent with the suggestion  that aleAnalytical vs. holistic thinking style differences may account for the variations in the executive networks found in this meta-analysis. Chinese participants have been shown to have a higher sensitivity to discrepant stimuli , whereas European participants have increased P3 responses to designated target events . This diAs illustrated by the two applications presented here, this database has a broad reach and can be utilized for many meta-analytic explorations. It is our intention to further develop and maintain this database and make it accessible for public use through a web interface. This resource will present users with public health information pertaining to attention and how it is affected in a multitude of clinical conditions and by various experimental manipulations . In the impetus for open science, the ANT Database will allow users to conduct meta-analyses on topics of their interest by centralizing the data extracted.As the meta-analytic explorations conducted through the database have been through the secondary use of data, various limitations are present. Participants in the regional explorations had been selected from the control condition of a multitude of studies, for which differences in task implementation cannot be controlled. Variables such as socioeconomic status and participant age may also play a role, while general age across the three regions was relatively consistent. Within the ADHD exploration, studies consisted of experiments that had participants from both conditions, who were roughly the same age (10.6 and 10.8), and who would have experienced identical tasks. However, standard deviation or error was not reported in all studies. While the stand-in standard deviation calculated from the remaining studies served as an adequate estimate, there is room for error in this approximation.The applications and utility of the database are extensive, and it can be a useful tool for conducting further meta-analyses and providing a resource to attention researchers, clinicians, and knowledge users. In older adults, attention performance has been shown to deteriorate with age, and impairments in visual attention are predictive of other cognitive and neurological decline . While pThe next step in this project will be to further develop the web interface of the database. Our initial focus will be to continue the data extraction of the remaining studies and bring the database up to date; however, future directions will be to create a tool for public health and global applications of attention. This interface will provide clinicians, patients, and interested parties a centralized resource and detail recent findings on topics of interest identified by public users that will be highlighted on the web interface. This resource will minimize the expenditure of researchers and clinicians to provide literature and resources to patients with attentional impairments, provide information to knowledge users in an easy-to-interpret way, and foster interdisciplinary and community collaboration.https://osf.io/edfqn/). The web interface for the ANT Database described in this manuscript is hosted at http://attentionnetwork.ca (presently under development).The data sets and analysis scripts for this study are available at (Ethical review and approval was not required for the study on human participants in accordance with the local legislation and institutional requirements. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.RK and SA contributed to the conception and design of this project. This research was conducted by SA under the direct supervision, guidance, and support of RK. ML performed statistical analysis and modeling of the data. All authors contributed to manuscript revision, and read and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.