Violent attacks on and interferences with hospitals, ambulances, health workers, and patients during conflict destroy vital health services during a time when they are most needed and undermine the long-term capacity of the health system. In Syria, such attacks have been frequent and intense and represent grave violations of the Geneva Conventions, but the number reported has varied considerably. A systematic mechanism to document these attacks could assist in designing more protection strategies and play a critical role in influencing policy, promoting justice, and addressing the health needs of the population.n = 176). One hundred and twelve healthcare staff and 185 patients were killed in these incidents. Thirty-five percent of the facilities were attacked more than once over the data collection period; hospitals were significantly more likely to be attacked more than once compared to clinics and other types of healthcare facilities. Aerial bombs were used in the overwhelming majority of cases (91.5%). We also compared the SAMS data to a separate database developed by Physicians for Human Rights (PHR) based on media reports and matched the incidents to compare the results from the two methods . Among 90 relevant incidents verified by PHR and 177 by SAMS, there were 60 that could be matched to each other, highlighting the differences in results from the two methods. This study is limited by the complexities of data collection in a conflict setting, only partial use of the standardized reporting tool, and the fact that limited accessibility of some health facilities and workers and may be biased towards the reporting of attacks on larger or more visible health facilities.We developed a mobile data collection questionnaire to collect data on incidents of attacks on healthcare directly from the field. Data collectors from the Syrian American Medical Society (SAMS), using the tool or a text messaging system, recorded information on incidents across four of Syria’s northern governorates  from January 1, 2016, to December 31, 2016. SAMS recorded a total of 200 attacks on healthcare in 2016, 102 of them using the mobile data collection tool. Direct attacks on health facilities comprised the majority of attacks recorded  were recorded on a standardized reporting tool using a mobile phone application.We found that there were more than 200 attacks on healthcare in 2016 in four northern governorates.In total, 112 health workers and 185 patients were killed in these incidents, and 176 of the attacks were on hospitals and other healthcare facilities.We compared data to another database maintained by PHR to show that no one methodology is capturing all of the incidents that have occurred.These numbers shed light on the extent of attacks on civilian health infrastructure and personnel in Syria.The study suggests that the utilization of a standard reporting tool can contribute to the depth and quality of the reported data, especially in capturing incidents that may not be found using media data.It also suggests that this method requires intensive training and support resources for successful implementation.The comparison between SAMS and PHR databases suggests that multiple methods of tracking attacks may be needed to identify all incidents.The study also highlights the need for more research and advocacy towards accountability and stopping the attacks. Acts of violence against healthcare facilities, transports, medical personnel, and patients are frequent but underreported in armed conflict –4. CliniSince the Syrian conflict began in 2011, an unprecedented number of attacks on hospitals and health workers has been reported –22 usingThere is widespread recognition that many attacks are not reported due to ongoing conflict, difficulty in accessing the site to gain quality information, or lack of clarity on what constitutes an attack . FurtherThis study sought to implement and test a method of collecting field data on the scope of and details about the attacks based on direct field reporting using questions centered on international human rights and humanitarian law. We also aimed to identify any characteristics that increase or mitigate vulnerability of healthcare facilities. We hoped to use this opportunity to evaluate the utility of a standardized field survey tool for documenting these attacks. To contextualize this documentation system, we aimed to compare the data to PHR’s database that uses media reports to track attacks on hospitals.We developed a standardized reporting questionnaire to document attacks on health in Syria based on a previously validated survey for tracking attacks on healthcare in Myanmar and grounded in the requirements of and definitions from international human rights and humanitarian law . These lThe questions covered attacks on four domains based on the requirements of law: (1) healthcare facilities and other settings where medical services could be provided ; (2) healthcare transports, including ambulances and vehicles carrying supplies and equipment; (3) healthcare personnel, including physicians, nurses, allied health professionals, and others providing clinical services; and (4) patients, both those that are already under care and those that seek care. The questionnaire also requested detailed information about an incident, including information about the victims; the perpetrator(s); date, time, and location; intentionality; type(s) of facilities; descriptions of the attack and type(s) of violence and weapon(s); damage inflicted; impact on functionality and service capacity; injuries; and deaths among patients and healthcare personnel, as well as narrative and image fields (the data collection tool is available from authors upon request). The questionnaire was translated into Arabic by the research team and verified by at least two other native Arabic speakers to ensure accuracy and clarity but, given resource limitations, was not formally back-translated. Revisions were discussed and made by consensus.The questionnaire was uploaded to a computer-based data collection application developed by the Magpi Mobile Data Service (Magpi)  and furtSAMS has documented attacks on health since 2014 in four northern governorates of Syria where it supports health services: Aleppo, Idleb, Homs, and Hama. These governorates have been the site of intense violence since the beginning of the war, with frequent attacks on civilian infrastructure, including health services . The repEach data collector was responsible for reporting on attacks in a specified geographical range where they lived. Data collectors identified incidents through a variety of methods, including mobile communication with fellow staff in SAMS-supported hospitals and the large network of health service providers in Syria, as well as the SAMS data managers who were notified of incidents directly by health workers, hospital administrators, witnesses, or through the health cluster.Once an incident was identified, the regional data collector visited the site of attack and sought out hospital staff, administrators, and witnesses to corroborate the incident and complete the survey. Data collectors were trained to only report on incidents after the attack had completely ceased and the area was secured. The data collectors interviewed informants using the reporting tool question fields and captured photographs and video of the incident, if relevant. They communicated basic information about the incident with SAMS data managers through a secure messaging system and were encouraged to characterize the full details of the incident using the Magpi program. SAMS data managers in Gaziantep oversaw the documentation process on each report and clarified any incomplete information with the data collectors. Data managers were responsible for verifying incidents with the health cluster network and with their personnel inside Syria. SAMS corroborated all incidents and details with multiple sources, including reports from other health staff, witnesses, and the health cluster, as well as video and photographs. Discrepancies in the data were reviewed by data collectors and data managers, and further investigation of those incidents was conducted using the resources described above.http://www.stata.com).The research team conducted analysis on the data collected using Magpi (51% of the incidents), as well as incident reports received via other forms of communication, such as messaging applications, emails, and personal communication. We attempted to understand trends in the data and study any variables that may have posed increased vulnerability for damage or injury. We looked at the times and dates of all incidents, presence of a red cross or other medical emblem, types of attacks and weapons, numbers of dead and wounded, resulting damage to a hospital and where damage took place, and the amount of time it was closed or had limited services. For targeted attacks on personnel and patients, we analyzed the type of attack and resulting injuries, deaths, and disabilities. We also compared hospital location and size to the frequency of attacks and the resulting damage to the facility and related casualties. Pearson chi-squared analysis was conducted to identify risk differences between groups throughout the analysis. This test was chosen because of its relevance to unpaired categorical data. We also attempted to understand challenges in using the mobile systematic data collection tool and reasons that data collectors did not use the mechanism for all incidents. We conducted analysis of the data using Stata v 14.4  matched. If the date was not an exact match, it needed to be within one week of the other.Possible match: If location or name of the hospital matched and the date was within one week of each other.Unique incident: Any incidents that do not match into any of the above category.We considered utilizing the capture–recapture analysis to calculate an estimate of the total number of incidents ,40. HoweSAMS collected data as part of its ongoing work to provide health services to people in Syria. The Johns Hopkins Bloomberg School of Public Health Institutional Review Board approved analysis of secondary data. To guarantee the confidentiality of data collectors and protect the identity of the facilities, no individual identifiers, names, or specific locations are used in this analysis.n = 122), Idleb (n = 49), Homs (n = 17), and Hama (n = 12) from January 1, 2016, to December 31, 2016 . Sixty-one percent (n = 122) of all attacks took place in Aleppo Governorate, of which 66.4%(n = 81) took place in Aleppo City.SAMS recorded 200 incidents of attacks on healthcare in 2016. Of those, 102 (51.0%) had completed reports on the Magpi application that allowed for more in-depth analysis. The attacks took place in the four northern governorates of Syria: Aleppo  and patients  were documented. An additional 433 injuries were documented among healthcare personnel  and patients . Overall, 30.0% (n = 60) of the incidents resulted in at least one injury and 34.5% (n = 69) in at least one death. Of the 90 incidents that involved at least one casualty (death or injury), the average number of deaths was 3.3 per incident, and 4.8 persons were injured per incident .We found attacks on all four domains within the SAMS database: facilities, transports, personnel, and patients. There were 176 incidents that primarily involved healthcare facilities, 16 that primarily involved transports and eight that primarily involved personnel. At least one attack was documented in every month except March 2016 . We noteThere were eight incidents in which healthcare personnel were attacked independent of strikes on facilities or transports. Among the personnel targeted, five incidents involved aerial bombs that hit physicians or other staff outside a hospital and one incident involved a physician who was shot by snipers and another killed by a landmine explosion. One incident involved the targeting of staff with chlorine gas.n = 120, 68.2%) involved hospitals. Outpatient clinics (n = 25), medical points (n = 4), and medical education facilities  were also attacked. Ancillary facilities (n = 24) included forensic centers, blood banks, specialty centers for physical therapy or preventative care, and medical administration .Ninety-four distinct facilities were attacked, of which 33 (35.0%) were attacked more than once in 2016 alone, accounting for 115 of the 176 attacks on facilities. Hospitals attacked more than once averaged 3.5 attacks in 2016. Two health facilities were attacked more than 10 times; both were large hospitals in Aleppo City. Hospitals were significantly more likely to be attacked more than once than other types of facilities (n = 14) were the result of aerial bombs. One ambulance was shelled by ground artillery, and another was physically attacked and looted.Sixteen of the recorded incidents targeted health transports. Fourteen of these targeted ambulances, and two were attacks on convoys. Most of the attacks on transports  than recording basic information, and the platform itself proved more challenging to use than we anticipated. They also noted that the use of a phone to document data appeared unfamiliar and disconcerting to some of the interviewees, who preferred a conversation to answering standardized questions.p = 0.995), location (p = 0.075), type of attack (p = 0.995), and total casualties (p = 0.08) between those attacks that were documented using the tool and those that were reported using the text messaging system. Of the 102 attacks recorded using the data collection tool, 90 were primarily attacks on facilities, eight on transports, and four on personnel. We found that data collectors spoke directly with healthcare personnel in 16 incidents, as well as other victims and/or witnesses who were not clinicians  in 86 of the incidents.Based on Pearson chi-squared testing, there were no notable differences in the domain (n = 80) of the 90 health facilities were damaged  as a result of the attack. Forty-nine facilities (54.4%) were forced to close for various lengths of time (11 were forced to close for two weeks or more and eight were closed permanently). Attacks that caused major damage did not have significantly more casualties (p < 0.349) compared to those with moderate and minimum damage. However, facilities with major damage were significantly more at risk of being closed (p < 0.001). Fourteen percent (n = 13) of facilities had a red cross, red crescent, or other medical emblem; there was no significant difference in repeated attacks (p = 0.208) or probability of closure (p = 0.558) between hospitals with and without emblems.We ascertained the level of damage resulting from the attacks as well as the ability of facilities and transports to function afterwards. Eighty-nine percent (n = 30) of the ambulances were taken out of service as a result of the attack, including 37.1% (n = 13) that were permanently destroyed. Eleven (31.4%) of the 35 ambulance systems displayed emblems.The mobile data-collecting platform also allowed for more nuanced understanding of overlapping domains of attack. Although there were 16 documented attacks primarily on transports in the full dataset and eight attacks primarily on transports in the systematic data collection subset, there were a total of 35 incidents involving attacks on transports within the 102 incidents in the subset analysis. Thirty-four of 35 of these involved aerial attacks on the transports (the remaining was secondary to artillery). Ten of these attacks (28.6%) occurred while the ambulance was in transit. Eighty-six percent (p = 0.026 utilizing the unpaired t test statistic). Although the incidents recorded occurred at all times of the day, a significantly higher proportion  occurred in the early morning hours, specifically between the hours of 05:00 and 08:00. We investigated differences in deaths (p = 0.149), presence of damage(p = .589), extent of damage (p = .363), and resulting closure between type of facility (p = .246). The only significant difference was among number of injuries (p < 0.002), but overall, there was no significant difference between facility types in these outcomes  in the four northern governorates, (2) involving attacks on facilities, and (3) confirmed PHR reports. Excluding incidents that did not fit this criteria, we identified 89 attacks confirmed by PHR and 177 reported by SAMS data collectors in 2016 (one incident that was documented primarily as a transport attack in the SAMS database was reported as a confirmed attack on a facility and a transport system in the PHR database). In one case, an incident in the PHR database was documented as two separate attacks . We therefore adjusted the PHR incident number to 90 be conservative . We wereThis study confirms the large number of attacks on health, particularly on health facilities, consistent with both PHR’s and WHO/Health Cluster findings for the period covered. The 200 attacks SAMS found in a region with fewer than 200 hospitals is a tragic testament to the long-term destruction of the health system in Syria. Using a prospective surveillance methodology, we found that most of the incidents impacted multiple domains; killing or injuring patients and personnel as well as destroying transport capacities while targeting a hospital was frequent. We also found that the personnel and patient casualties consistently rose and fell with the frequency of hospital attacks over time. During the period covered, hospitals in the city of Aleppo suffered a significant portion of the attacks. Repeat attacks on hospitals were frequent and highlight the vulnerability of these facilities, especially larger centers, to bombardment, possibly because they are easily visualized and identified. Many other types of facilities, such as medical schools and blood banks, were also attacked or destroyed. While we identified primarily infrastructure attacks, many staff and patients were also killed or injured. On average, more than three people were killed in each incident involving at least one casualty.These findings suggest that the number and severity of attacks on healthcare infrastructure and personnel in Syria are the most extreme example of a disturbing worldwide phenomenon. In 2016 alone, health facilities and health workers were attacked or subject to obstruction or interference in at least 23 countries in conflict . Sound dThere is wide agreement that sound methods to track attacks on and interference with healthcare facilities and personnel are essential. In collaboration with SAMS, we developed a standardized questionnaire for reporting attacks on healthcare in Syria that complements other methods for documenting attacks developed by PHR and by the WHO health cluster for northern Syria. Using the questionnaire, SAMS reported 102 attacks in the northern governorates of Syria, but our analysis of all of SAMS’ incident data revealed that the tool was not used in nearly half of the reported incidents. This experience suggests that it is challenging to utilize a systematic, field-based data collection mechanism consistently during times of intense conflict but that, when it is used, it provides valuable, detailed information that can inform advocacy and policy. We highlight that use of the data collection tool permitted comparisons in the attacks based on size and type of health facility, presence of an emblem, operational capacity after the attack, and source of information. It allowed for more nuanced information on attacks that involved multiple domains of health services. However, use of the tool was considered lengthy and time consuming by some of the field data collectors. Use of this tool was feasible in this context, but to be used for each incident, we believe it requires a relatively high level of administrative, technological, and epidemiological support. We also believe that simplification of the questionnaire would be helpful, even at the cost of the absence of data collection on certain topics. The research team has reviewed these concerns and is prepared to modify and revise the tool to achieve the right balance between comprehensiveness and ease of use.Using systematic data collection, we found that there is a significantly increased risk of multiple attacks on larger tertiary care hospitals. A more nuanced understanding of the damage and destruction caused by these attacks is important in order to better gauge the health services that these communities might require going forward. We note that only a small percentage of facilities and transports had a medical emblem, suggesting in a context where emblems historically have protected from attack that they may be perceived to represent a vulnerability in Syria. Similarly, the massive scale of attacks on hospitals in particular may represent the ease of distinguishing these structures from the air and highlight the paradoxical humanitarian framework at play in Syria, where signs of humanitarian operations may actually be a risk for attack.In collaboration with PHR, our findings also suggest that no one methodology currently used to document attacks in Syria is sufficient to identify the full scope of the assaults. SAMS documented 177 attacks on health facilities, and PHR documented 90 confirmed incidents in the comparable geographical region and time frame, but PHR received reports of at least 234 relevant incidents in its aggregate database that includes both verified and unverified attacks. The reasons for the difference is likely a product of the limitations of the methods used. For on-the-ground reporting, such as that used by SAMS, the limitations are likely the inability to access all areas to take reports; for the primarily open-source reporting used by PHR, the limitations are likely the result of lack of media reporting of all incidents, as well as the high standard for corroboration required by PHR. By matching the incidents, we found that only 60 of the incidents were matched between the two datasets. Thirty of the PHR incidents and 117 of the SAMS incidents were not found in the other dataset. These figures highlight the difficulty in capturing all incidents against healthcare in a challenging humanitarian context and illustrate the attacks that are likely being omitted by any single data collection mechanism. Collaborations among partners can provide in-depth detail while also helping to establish the full breadth of the attacks. The UN Health Cluster for northern Syria, of which SAMS is a member, utilizes such a collective methodology and has reported 158 verified incidents between November 2015 and December 2016 [A subsidiary finding is that the data collection program appears to have empowered local communities with whom data collectors interacted to contribute to the documentation of incidents. This type of on-the-ground system can potentially help energize communities, present useful, real-time data, and contribute to advocacy and diplomatic channels in the context of some quantitative data. Our colleagues at SAMS have used this data to inform their advocacy and programming efforts.The study has some important limitations. We utilized a previously validated survey tool based in international humanitarian law to develop a standardized approach to documenting attacks on health globally. However, all conflicts are unique, and further work may be needed to adapt the tool to capture attacks in other settings.Documentation in this challenging, complex, and violent context of civil conflict is limited by the accessibility of the hospitals and the willingness of staff, victims, and witnesses to discuss their experiences, leading to under- or over-reporting. SAMS utilized data collectors who live and work among the communities where they documented attacks. While this familiarity with the culture and community may have mitigated any hesitancy to discuss violence, witnesses may still have been reluctant to share information due to personal and/or security risks. Additionally, the data collectors were limited in their ability to document attacks during times of high risk to their own safety or when excessive attacks in a short time frame would limit their ability to visit various incident sites. We note that while reports from major incidents or attacks on larger facilities may have been more rapidly transmitted than those on smaller facilities, data collectors and SAMS staff made great efforts to ensure that attacks on smaller facilities and individuals were regularly surveilled.The data on the overall number of attacks as reported by SAMS come from two different collection methods: the simple reporting of key details about an event by text messaging and more in-depth information about incidents available through the systematic data collection tool. It is possible that there were qualitative differences between the attacks reported via the systematic data collection tool and those reported elsewhere. In our review of the underlying incidents, we did not identify any relevant patterns in how a particular type of event was reported; however, it is possible that they exist. The use of mobile technology, though it rendered more details about specific incidents, was not used in about half of the incidents, suggesting that the program will require further revisions and training to ensure that it is used more consistently. Sporadic interruptions of cellular reception and internet connectivity were also reported to limit use of mobile data collection and transmission.We note that this program did not include a formal system for secondary or tertiary verification of incidents. However, SAMS data managers utilized a variety of methods to ensure data quality, including checking all incidents among the health cluster network, corroborating with other field staff and health personnel, communicating back and forth with data collectors, and gathering photographic and video evidence to ensure data quality. While there may be a role for the larger health cluster to use formal mechanisms and external reports to verify each incident, SAMS’ role was to create a reliable and accurate system of original reporting. Nevertheless, the findings of this study are based on reports that have been extensively checked and authenticated. We did not discern any differences in verification between Magpi-reported incidents and others.Because of the frequency of bombing and shelling of health facilities, the majority of our data involve such events. While we documented some incidents of attacks on personnel independent of facility attacks, our data likely understate these assaults, as well as obstructions of access to care, since they may garner limited attention in comparison to incendiary strikes. The survey tool was developed to document attacks across all domains, which may be more frequently utilized in other violent conflicts. There is also a risk of reporting bias. Although data collectors documented attacks within hours or, at most, a few days of an attack, there may be recall bias or other reporting bias in the surveys. Attacks on larger health facilities may be more likely to be reported, while attacks on smaller facilities may be underreported, potentially because there is less impact or fewer staff or witnesses to report the incident. Another source of possible bias is in the political views of data collectors and witnesses. In almost all cases, photographic evidence and multiple victim corroborations have assisted in mitigating the likelihood of bias.We evaluated the SAMS and PHR data for independence in their methodologies. SAMS staff does not coordinate with PHR for its data collection or vice versa. PHR’s data was retrospectively reviewed, as they do not have any staff on the ground in Syria and utilize social and news media accounts of attacks. SAMS data collectors arrive at the scene of the attack and use nonmedia means of obtaining information on attacks on health, including eyewitness accounts, networking with administrators and health staff, and private SAMS messaging groups. Ideally, our comparative analysis would have utilized more than one partner, but given the constraints of setting, limited collection of this type of data, and the challenges in collecting detailed information on attacks, we believe our approach offers the most comprehensive understanding of attacks on healthcare in Syria to date.This study shows the potential contribution of employing field data collectors in documenting attacks on healthcare. Along with reporting by health cluster organizations (as WHO has shown) and analysis of photographic, video, media, social media, and other materials (as PHR has done), dedicated field data collectors can collect direct and powerful evidence of attacks. Standardized questions can yield detailed, consistent information, and the use of a mobile application can allow secure and quick transmission of data.Tracking attacks on healthcare is vitally important for three purposes. First, sound data about attacks is essential to help the global community know exactly what attacks are taking place, where they are taking place, what their impacts are, and, in some cases, who the perpetrator is. Second, it is essential to stimulate action at the international level that can prevent future attacks, promote investigations, and ultimately hold perpetrators accountable. Third, it can assist organizations in designing harm mitigation strategies, as SAMS has previously attempted . The ongThe analysis also suggests a far higher level of attacks on healthcare in Syria than previously reported. We highlight that, beyond the violent injuries that are documented in this manuscript, there must be an informed discussion of the consequence for mortality and morbidity that results from the destruction of the healthcare infrastructure, including from communicable diseases, lack of preventative care, exacerbations of chronic conditions, limited-capacity prevention programs, and the fear of seeking out healthcare services when they are seen as a target for attack.This study also demonstrates the capacity of locally based organizations and data collectors, in collaboration with physicians and other health staff, to contribute to documentation of attacks on health using a mobile systematic data collection application and act as potent agents to report and chronicle this violence.The UN Security Council, as part of Resolution 2286 passed on May 3, 2016, “condemns acts of violence, attacks and threats against the wounded and sick, medical personnel and humanitarian personnel … as well as hospitals and other facilities and demands that all parties of conflicts comply with their obligations under international law” . WHO is S1 Fig(TIF)Click here for additional data file.S1 Data(XLSX)Click here for additional data file.


Chlamydia trachomatis, scars on the inside of the eyelids contract, disrupting the lid margin and causing the eyelashes to rotate inwards until they rest against the eye. With each excruciating blink, the lashes damage the sensitive cornea leading to corneal opacity and irreversible blindness.Trachoma is a progressive and miserable disease. Initiated by frequent and repeated ocular infections with the bacterium Trachoma has been with us for a long time; it is among the conditions catalogued in the oldest medical text—the Ebers Papyrus. Taking into account life expectancies too short to allow many people to develop cataracts, trachoma was likely the leading cause of blindness before the Industrial Revolution and the consequent increase in life expectancy.In our view, the integrated and holistic SAFE strategy to eliminate trachoma—a strategy based on surgical correction of misplaced lashes, the mass distribution of donated antibiotics, and the promotion of water, sanitation, and hygiene (WASH)—makes the program the most compelling of the neglected tropical disease (NTD) elimination programs. SAFE implementation goes far beyond “just” putting trachoma in the crosshairs for elimination as a public problem. Whilst we are used to the concept of collateral damage, the SAFE strategy comes with considerable collateral benefits. Such benefits include the improved quality of life associated with surgery, particularly for patients who are yet to suffer loss of vision . An annuwww.trachomaatlas.org), the scale of the task ahead of us could be visualized. The target of eliminating trachoma set in 1998 suddenly felt real and achievable. Now we were not shooting in the dark, new financial resources were made available (largely from the United States and United Kingdom governments and the Queen Elizabeth Diamond Jubilee Trust), and Pfizer Inc. once again doubled the size of its donation to over 100 million doses a year in 2016  fall below 5% and stay below 5% for two years. In calendar years 2014 and 2015, 143 health districts with a total population of 29.7 million people reached this elimination target. In addition, a new country-level validation process has been developed, and Morocco joins Oman in being validated as having eliminated trachoma as a public health problem by the World Health Organization [Endemic districts are considered to warrant MDA with azithromycin until such time as the clinical signs of active disease in children aged one to nine years (TFnization . Of the 1-9, countries will be validated relatively slowly. However, this masks the remarkable progress being made in hundreds of districts around the world. By the year 2020, we estimate that at least 70% of the endemic districts will have reached the transmission target of TF1-9 below 5%. This forecast will allow the global program to identify areas where an infusion of additional funding, an alternative treatment strategy, or other creative approaches will be required in order to speed the achievement of our elimination goals.The trachoma community is now working to finalize a forecast model, based on conservative assumptions, that will allow us to determine when the global elimination of trachoma will be achieved. Because a country cannot declare elimination of trachoma until the very last of its endemic districts is demonstrated to reach and remain below 5% TFThe astonishing progress shown in the global program demonstrates that trachoma can be eliminated as a public health problem. The targets can be reached. People need no longer live with the prospect of having their corneas scratched out by their own eyelashes. The global trachoma program is public health at its best. The allure of “getting to zero” and freeing humankind from a disease that has plagued it for millennia is inspiring, but considerable challenges remain .Some districts, most notably in northern Ethiopia and central Tanzania, are responding to intervention slower than the rest of the world: ten or more years of intervention with many rounds of MDA are often insufficient to reach the elimination target . AlternaFor trachoma to be eliminated, every endemic community must be reached. The most marginalized people—indigenous tribes in the Amazon forest and hunter-gatherers in Africa, refugees and internally displaced people, and those living in areas of armed conflict—must be reached, in addition to the settled populations. Sadly, the most marginalized people and those living in war-torn areas are often those most at risk of neglected tropical diseases.The evidence base for the global program has been developed and refined largely on the backs of ongoing national programs: we have been building the ship as we sailed it . AdequatThe global program has made tremendous progress. We have come further than we could possibly have hoped at the launch in 1998; but as strong as the global program is, we are also fragile. Any significant change in philanthropic philosophy, power, and politics can trump public health gains. The global program remains dependent on strong political will to succeed in endemic countries, the active participation of over 200 million people at risk, an unfaltering supply of donated medicine, a continuous pipeline of donor funds, increasing support to operational and basic science research, and access to all endemic areas. Despite the challenges, it is possible to eliminate trachoma as a public health problem. The world deserves our continued efforts and best work now so that future generations will never know the pain and suffering of trachoma.No funding was provided for the preparation of this opinion piece. This opinion piece was prepared by PME, PJH and VS in their personal capacity. The views and opinions expressed are the views and opinions of the authors themselves and do not reflect the opinions, views or policy of the Task Force for Global Health, Pfizer Inc. or the International Coalition for Trachoma Control.


The distributions of income and health within and across countries are changing. This challenges the way donors allocate development assistance for health (DAH) and particularly the role of gross national income per capita (GNIpc) in classifying countries to determine whether countries are eligible to receive assistance and how much they receive. Informed by a literature review and stakeholder consultations and interviews, we developed a stepwise approach to the design and assessment of country classification frameworks for the allocation of DAH, with emphasis on critical value choices. We devised 25 frameworks, all which combined GNIpc and at least one other indicator into an index. Indicators were selected and assessed based on relevance, salience, validity, consistency, and availability and timeliness, where relevance concerned the extent to which the indicator represented country’s health needs, domestic capacity, the expected impact of DAH, or equity. We assessed how the use of the different frameworks changed the rankings of low- and middle-income countries relative to a country’s ranking based on GNIpc alone. We found that stakeholders generally considered needs to be the most important concern to be captured by classification frameworks, followed by inequality, expected impact and domestic capacity. We further found that integrating a health-needs indicator with GNIpc makes a significant difference for many countries and country categories—and especially middle-income countries with high burden of unmet health needs—while the choice of specific indicator makes less difference. This together with assessments of relevance, salience, validity, consistency, and availability and timeliness suggest that donors have reasons to include a health-needs indicator in the initial classification of countries. It specifically suggests that life expectancy and disability-adjusted life year rate are indicators worth considering. Indicators related to other concerns may be mainly relevant at different stages of the decision-making process, require better data, or both. Key MessagesStakeholders considered needs and health needs to be the most important concern to be captured by country classification frameworks for development assistance for health (DAH), followed by inequality, expected impact and domestic capacity.Integrating a health-needs indicator with gross national income per capita (GNIpc) in the classification framework makes a significant difference for many countries and country categories—and especially middle-income countries with high burden of unmet health needs—while the choice of specific indicator makes less of a difference.Donors have reasons to include one health-needs indicator in the initial classification of countries, and both life expectancy and disability-adjusted life year rate are indicators worth considering.For most donors, indicators related to other concerns—including equity—may be mainly relevant at different stages of the decision-making process, require better data, or both.et al. 2017a). It is also well known that GNIpc does not directly account for the distribution of income, health, and health services within countries , which are often characterized by substantial inequalities in income, health and access to health services . These tountries .Together, this calls for new frameworks for classifying countries for the allocation of DAH; frameworks that go beyond GNIpc and incorporate a broader set of indicators. In response, the Equitable Access Initiative (EAI) was initiated in February 2015 to explore such frameworks. A group of researchers affiliated with the Norwegian Institute of Public Health (NIPH) was commissioned to provide input to the Initiative as one of four analytical teams. The specific objective of the NIPH team was to explore frameworks for classifying countries based on characteristics relevant to decisions on DAH. In the initial work, this was framed in terms of ‘external financing for health’, which includes traditional forms of DAH. The classifications were meant to guide donors in determining countries’ priority for DAH, which donors do both through decisions on what countries are eligible and through decisions on how much assistance each eligible country should be offered. This article presents the methods developed and employed by the NIPH team, reports and discusses the findings, and lays out recommendations for donors.We developed and used a stepwise approach to the design and assessment of frameworks. This was done alongside a series of interviews and consultations with stakeholders, which we further discuss below. These various activities were pursued in parallel and informed each other.The stepwise approach to the design and assessment of frameworks comprised four steps: delineation of normative basis; screening of indicators; design of candidate frameworks; and assessment of frameworks. The approach was developed on the basis of a review of previous efforts of framework and index construction in various fields and with the aim of exposing the key choices involved in the design and assessment of classification frameworks.Decisions concerning DAH are inherently based on value choices, but these are often left implicit or poorly defined. We sought to clearly delineate a normative basis for the allocation of DAH by identifying and defining the basic, underlying country-level concerns that motivate the allocation of aid by donors among partner countries. To this end, we reviewed the literature on health financing, development assistance and distributional justice, and we elicited stakeholders’ views through consultations and interviews . These aWe identified candidate country-level indicators for classification frameworks by first crafting a list of potential indicators see . This liWe then proceeded to screen the indicators on the basis of relevance, salience, validity, consistency, and availability and timeliness . RelevanWe designed 25 candidate frameworks to allow for broad comparison and analysis of key value choices. We sought simple frameworks in the form of indices that were easy to understand for stakeholders, and we sought frameworks that together covered a wide range of indicators and all the basic concerns.et al. 2017b). For example, according to a common rule for GNIpc, rank and priority decrease monotonically with increases in GNIpc. The third sub-step was min–max normalization , which is in line with the World Bank classification and most eligibility thresholds and allocation policies employed today. Beyond GNIpc, most of the indices we constructed included only one additional indicator. Each indicator was chosen from the long list of indicators based on the screening criteria and the goal of comprehensiveness for the final set of candidate frameworks. A detailed description, including data sources, of the indicators integrated in one or more frameworks are provided in Appendix 1. We next specified the prioritization rule—a step that is often left implicit. The prioritization rule specifies what happens to a country’s priority for DAH when the country’s value of a given indicator increases . Finally, to aggregate two or more products of a weight and a normalized indicator into a composite index, we employed linear aggregation, that is, straightforward summation of these products . Although rankings were generated for all these countries, we concentrated on five focus countries for illustrative purposes: Ethiopia, India, Mali, Nigeria and South Africa. This set was chosen to jointly cover different levels of income  and upper–middle-income countries (UMICs)), health expenditures, health service coverage, health outcomes, and inequalities in income and health. This set of countries should thus help demonstrate key features of classification frameworks. Our initial sample of countries included all countries classified as low-income countries (LICs) and middle-income countries (MICs) for which GNIpc was available . While focus on the bottom quintile is common, the choice of a 20% threshold is of course somewhat arbitrary. The countries affiliated with each category are listed in Appendix 2. Implications across income classes were examined because much of the debate is framed in terms of the role of MICs compared with that of LICs. Similarly, implications for the two other country categories were examined because concerns for countries with profound health needs and the relationship between economic capacity and disease burden figure prominently in the current debate. Yet, it is worth noting that 96% of the 20% of countries with the lowest GNI-DALY ratio in our sample are classified as LICs. The relationship between this ratio and income class has been examined in more detail elsewhere, including in the specific context of AIDS  for all the indicators pertaining to the framework category were included. This strategy was pursued to reduce the effect of missing values countries’ change in rank.We elicited the views of stakeholders through consultations, interviews and an online survey. Findings from the online survey is reported by Grépin et al in this issue. Six consultations were organized by the EAI in Geneva or New York. Here, we presented preliminary plans, methods, and findings and received input from a wide range of stakeholders. These represented the EAI Convening Partners, multi- and bilateral donors, partner countries, civil society organizations, the private sector and academia.To gather further input, we conducted twenty semi-structured interviews with stakeholders in August and September 2015. Interviewees were identified through a screening of members of boards and committees at the Global Fund to Fight AIDS, Tuberculosis and Malaria and at Gavi, members of the EAI Technical Working Group, members of the EAI Expert Panel and experts known to the team or with published work in the field. We selected the individuals to invite for an interview on the basis of their expertise on topics central to this study and their contribution to diversity in the overall sample of interviewees. Nineteen of the interviews took place over the phone, and one was conducted face-to-face. Nine of the 20 interviewees were members of either the EAI Conveners’ Technical Working Group or the EAI Expert Panel. The stakeholders interviewed represented academic institutions (six), civil society or non-governmental organizations (four), multilateral organizations (four), bilateral donors (three), partner-country governments (two) and a philanthropic foundation (one), with several stakeholders representing more than one institution. Partner country stakeholders represented various institutions in India, Pakistan, South Africa, Thailand and Zimbabwe. The interviewees held senior positions within their institutions, most with responsibility for policy, global health, access, human development or a combination.The interview questions were developed in dialogue with the EAI. The interviews concentrated on stakeholder views on classification frameworks and characteristics relevant to decisions on DAH. Questions pertained to the purpose of such frameworks, the role and relevance of four concerns  and indicators.Primary findings were of four kinds: stakeholder views, menu of candidate frameworks, indicator evaluations and framework implications. In addition, the stepwise approach developed can be useful for donors and stakeholders in their design or assessment of frameworks.Stakeholders reported views pertaining to the role of frameworks, relevant concerns, and relevant indicators.initial guide to decisions on DAH. This included decisions on eligibility, terms of contributions, and the size of allocations. Many respondents asserted that one also needs a framework for choosing the modality of assistance, e.g. whether to focus on financial assistance, technical assistance, capacity building, or advocacy. At the same time, most respondents emphasized that the role of classification frameworks in the overall decision making progress is circumscribed and that a wider set of factors needs to be considered after a classification framework has been applied. These included various qualitative factors, for example related to a country’s economic and health policies, social issues, tax systems and performance; respondents perceived as less apt for being captured by a framework.Respondents considered frameworks for classifying countries to be potentially useful as an Respondents generally emphasized that the frameworks needed to be simple and transparent. At the same time, several respondents noted the risk of frameworks being oversimplified and insufficiently sensitive to the complexities in the allocation of DAH.Respondents were directly asked about four areas of concern: needs and health needs, capacity, expected impact and inequality. Of these, needs and health needs was identified as the most important by stakeholders, followed by inequality. Several respondents asserted that we must avoid ‘double penalty’, where neither the national government nor external donors accepts responsibility for poor people with unmet health needs.how to meet needs. This included questions about time horizon and modality of assistance. Capacity was generally considered the least important of the four concerns, and many emphasized aspects of capacity that they perceived to be different from ‘ability to address health needs without external financing.’ For example, several saw capacity as primarily linked to the strength of the country’s health system and infrastructure, independently of the country’s need for external assistance.Several stakeholders suggested that considerations of capacity and expected impact are important, but often in ways external to the initial classification of countries and thus to the classification frameworks. For example, it was suggested that capacity and expected impact help address questions about Finally, several stakeholders made a distinction between funding by bilaterals and multilaterals and expressed that the former have more flexibility but are also more subject to political verities and geopolitical considerations.Respondents deemed GNIpc to be relevant, but emphasized the need to go beyond this and consider additional factors. The statement by one interviewee that GNIpc is the ‘least worst indicator’ represented a view shared by many respondents. The interviewees noted that GNIpc is updated every year, available for all countries, easily understood, correlated with other indicators and transparent.Although most acknowledged the role of GNIpc as a principal indicator, there were caveats and concerns. A number of these were related to the classification of MICs. Here, stakeholders noted the need for sensitivity to the following issues: dramatic and rapid shifts in GNIpc levels that may prematurely suggest greater capacity; the limitations of GNIpc in identifying the extensive health needs and poverty in MICs ; and the importance of broader indicators and criteria designed to incentivize domestic investment in health (rather than displacing domestic spending) or identify gaps in coverage and capacity. More generally, and in line with their ranking of concerns, respondents identified measures of health needs and inequalities as the most important indicators to include in a classification framework alongside GNIpc.Based on the screening of indicators, 25 candidate frameworks were generated, as shown in et al. in this issue). Specifically, we assigned a weight of 0.1 to GNIpc, 0.3 to life expectancy, 0.4 to inequality in life expectancy and 0.2 to SBA.As exhibited in We found that the indicators integrated in one or more frameworks varied considerably in terms of relevance, salience, validity, consistency, and availability and timeliness. The health-needs indicators generally scored well against relevance, although the applicability of under-five mortality rate (U5MR) and under-60 mortality rate (U60MR) may be restricted by them only capturing mortality before the age of 5 and between the ages of 15 and 60, respectively. In contrast, life expectancy, healthy life expectancy (HALE), disability-adjusted life year rate (DALYR) and age-standardized disability-adjusted life year rate (DALYR_AS) are sensitive to all deaths, at all ages, and from all causes. At the same time, the latter three of these differed from the other indicators by integrating morbidity in addition to mortality. The gap measures DALYR and DALYR_AS also stood out by facilitating decomposition of health needs with regard to cause, risk factor and age structure  generally scored less well against relevance. A key reason was that the relationship between each of the indicators and rank in a classification framework appeared more convoluted than for the health-needs indicators. We also found that it is tricky to draw the line between government choice and external circumstances  and thatThe impact indicators scored relatively well against validity, consistency, and availability and timeliness, with the U5MR-related indicators performing somewhat better than those linked to SBA. Relevance for a classification framework was found to be the main challenge for these impact indicators, even for donors focusing on child or maternal health. While expected impact was found to be a relevant concern, the link between the impact indicators and rank in a classification framework appeared far from straightforward . One reaThe disease-specific indicators were found to be too narrow for donors with health mandates broader than HIV, tuberculosis, or maternal mortality. Overall, these indicators scored moderately well against validity, consistency, and availability and timeliness.The category of other indicators is a heterogeneous group. This was also reflected in their evaluation. Inequality was generally found relevant for the allocation of DAH. However, the relevance of inequality indicators for the classification of countries was challenged by the complex relationship between inequality levels and priority for DAH. Greater inequality may indicate higher needs and suggest higher priority, but greater inequality may also indicate higher capacity to address needs—including through redistribution—and thus suggest lower priority . In addiThe final three indicators—SBA; third dose of vaccine against diphtheria, tetanus, pertussis (DTP3); and out-of-pocket payments (OOPPs)—were found to partly signal need. However, the relevance of SBA and DTP3 in a classification framework was also found to be challenged by their restricted focus, which may be too narrow for many donors. All three indicators were found to be linked to data of quite low quality. The Spearman coefficients for all the 25 frameworks are shown in We found that integrating a health-needs indicator with GNIpc made a substantial difference for many countries and country categories, while the choice of health-needs indicator made less of a difference.As for general trends, the Spearman coefficients for correlations between GNIpc and each of the health-needs frameworks were all fairly high, ranging from 0.89 (U60MR), via 0.90 (life expectancy (LE)) and 0.92 (DALYR), to 0.93 . Correlations between GNIpc and each of the health-needs indicators were obviously lower, as shown in While correlations between GNIpc and each of the health-needs frameworks were fairly high, the departures from perfect correlation still allow for marked changes in rank for individual countries. Nigeria and South Africa got a substantially higher rank and thus priority, whereas Ethiopia got a significantly lower rank. For India and Mali, the changes are less pronounced or more mixed. The figure also demonstrates that the differences across health-needs frameworks for the most part were quite small.With regard to the categories of countries, On an average, LICs got a somewhat lower rank when moving from GNIpc alone, irrespective of the health needs framework. Conversely, the LMIC and UMIC groups got a higher rank from any move away from GNIpc alone, but this increase was small. The countries with the lowest life expectancies experienced a quite substantial increase in rank across all health-needs frameworks. For the countries with the lowest GNI-DALY ratios, however, the inclusion of a health-needs indicator led to a slight decrease in rank. In line with the findings for the five focus countries, the differences across health-needs frameworks within each country category were quite small.Compared with the health-needs frameworks, there were more variation within the capacity frameworks, within the impact frameworks, and within the other two-criterion frameworks in how the different frameworks affected different countries and country categories. As shown in As for the health-needs frameworks, even high correlation coefficients allow for substantial changes in rank for individual countries. Nigeria and South Africa got a substantially higher rank when moving from GNIpc to any other framework, except for the debt framework. A similar but less marked pattern applied to Mali. Conversely, Ethiopia and India experienced a lower rank when moving to any other two-criterion framework, except the cU5MR framework for India. For the multi-criterion frameworks (MCF_EQ and MCF_SU), changes in rank were pronounced for Nigeria and South Africa. The difference between the multi-criterion framework with equal weights and that with survey-informed weights was modest.With regard to the country categories, This figure demonstrates some general trends. Among the income classes, all moves beyond GNIpc alone led to a lower rank on average for LICs and a slightly higher rank for LMICs and UMICs as groups. Among the two other categories, the 20% of countries with the lowest life expectancies got a higher rank, with the exception of the debt framework, whereas the countries with the lowest GNI-DALY ratios consistently got a lower rank. These patterns of change apply for the most part also to the frameworks not shown in The findings from this study can inform donors in the assessment and reform of their allocation policies, as well as stakeholders and researchers contributing to such efforts. Our findings suggest that health needs, domestic capacity, expected impact and equity are all concerns that most stakeholders find relevant and that many of these stakeholders rank ‘needs and health needs’ as the top concern. The findings further suggest that nearly any departure from GNIpc alone will disfavour LICs as a group. While revision of a classification framework needs not be a zero-sum game, this finding serves as a reminder that any effort to target MICs should be accompanied by a close look on the consequences for LICs. The stagnation of DAH in recent years only underscores the importance of a careful examination.Our findings suggest that addressing health needs is generally considered a key objective for DAH and that a general health-needs indicator can be relevant for many institutions. The findings further suggest that the indicators integrated in the six health-needs frameworks  all perform well in terms of relevance, salience, validity, consistency, and availability and timeliness. The comparison of frameworks indicates that including a health measure in the framework makes a substantial difference for many countries and country categories and that it improves the ranking and priority of countries with large unmet health needs in particular. Against this background, donors have reasons to combine GNIpc and one health-needs indicator for the initial classification of countries. If this is done, donors and other stakeholders may want to pay particular attention to any negative effects on LICs and provide safeguards where needed.The findings also indicate that what specific health-needs indicator is used makes less of a difference than whether or not such an indicator is included at all. Moreover, no single health-needs indicator appears to be clearly superior to all others in terms of relevance, salience, validity, consistency, and availability and timeliness. However, our analysis suggests that both life expectancy and DALYR are good candidates for being included in a classification framework and that donors may want to pay particular attention to these if they want to use a single broad health-outcome measure. As described above, both life expectancy and DALYR are sensitive to all deaths, at all ages and from all causes. Life expectancy is already a familiar and well-tested measure in numerous contexts, including as one of three dimensions of the Human Development Index, where GNI per capita is another dimension . MoreoveFindings from the literature review and the interviews suggest that domestic capacity, expected impact and equity are also important considerations when allocating DAH. However, none of the examined indicators was clearly suitable for inclusion in a classification framework when judged against the criteria of relevance, salience, validity, consistency, and availability and timeliness. While most the indicators were linked to general concerns that were found to be relevant, the relevance of the indicators specifically for use in a classification framework was less clear. A key reason is that the relationship between each of the indicators and rank in a classification framework appeared more convoluted than for the health-needs indicators. Many of the other indicators were also found to score relatively poorly on validity, consistency, or availability and timeliness.Indicators other than the health-needs indicators can play an important role in the allocation of DAH even if the assessments above are accurate. First, these other indicators may be part of the classification framework used by donors with quite specific mandates. For example, the HIV prevalence rate may be key for a donor specifically focusing on HIV/AIDS. Second, one or more of the other indicators may be part of comprehensive multi-criterion frameworks, where the combination of indicators counteract perceived shortcomings of the individual indicators. Third, the other indicators may play a role at stages in the decision-making process different from the initial classification of countries. In particular, indicators of domestic capacity (other than GNIpc), expected impact and inequality may be considered as part of more discretionary assessments at the program or project level. These can be assessments in the review of applications or assessments during the implementation phase.For indicators found to be relevant but poor performers in terms of validity, consistency, or availability and timeliness, donors and other stakeholders should identify the most relevant indicators and increase their efforts in the development of new metrics, collection of data or both.Some of the limitations to this study apply to most or all classification frameworks. One is that for nearly any normative view, it is impossible to combine all relevant concerns and indicators into one simple framework or index. Most or all frameworks also struggle to deal adequately with incentives and the problem that if poorer levels of an indicator imply higher priority for DAH, countries’ incentives to improve on this indicator is likely to be reduced. Similarly, most or all frameworks fail to deal adequately with pockets of poverty and unmet health needs. Here, one way forward could be to use health outcome data for the poorest quintiles, for example from Demographic and Health Surveys.Pursuing research in the context of a process like the EAI comes with both strengths and weaknesses. One strength is that the research is oriented towards issues of direct interest to policy makers. One weakness is independence and the risk that the research leaves important but controversial issues unaddressed. In the present study, this was the case with regard to the study of explicit eligibility thresholds. However, while some of the limitations of our approach were the result of restrictions in the mandate given by the EAI, most were the result of deliberate trade-offs in the face of time constraints.First, we focused on frameworks relevant to decisions on eligibility for financial assistance and the size of allocations and frameworks meant to apply early in the decision-making process. Future studies should examine normative bases and frameworks for decisions on the modality of assistance, non-financial support and the financing of global public goods for health. In addition, for decisions on modality and non-financial support, the development of robust inequality measures may be particularly important.should do, findings from the interviews can provide useful input to donors’ own deliberations. Future studies may explore concerns and indicators in greater depth and involve larger and more representative samples of stakeholders. Another article in this series reports on the online survey described above, which involved a larger number of stakeholders and examined the relative importance assigned to different indicators in greater depth than in the present study .Second, the interviews and survey were based on a limited and non-representative sample of stakeholders. There were also considerable variation around several of the typical responses. While the interviews do not provide the ‘true’ answers for what donors Third, we used GNIpc as the starting point and a component of all frameworks. This does not preclude putting less weight on GNIpc than other indicators in the frameworks, but our approach is less relevant for those who would like to entirely exclude GNIpc.Fourth, we could only conduct a basic assessment of the many indicators’ salience, validity, consistency, and availability and timeliness. A valuable next step would be a fuller, in-depth assessment of the quality of the key candidate indicators for guiding the allocation of DAH. Such an exercise could be modelled on previous endeavours in neighbouring areas, such as the recent assessment of indicators by the Primary Health Care Performance Initiative .Fifth, we were unable to examine all relevant indicators, all relevant combinations of indicators and all plausible prioritization rules. We believe, however, that the indicators and frameworks examined in this study cover an informative range of alternatives and that the stepwise approach developed can be useful to donors also independently of the specific indicators and frameworks addressed here. Given the importance of generic health-needs indicators, future studies may critically examine the strengths and weaknesses of these indicators. Using assessments of two-criterion frameworks as the starting point, future studies may also explore more complex options. This may include examination of how well-established multi-criterion frameworks, such as the allocation formula used by the International Development Association and the criteria set used to identify Least Developed Countries, can better integrate a concern for unmet health needs.Sixth, there is no agreement on the best method for framework or index construction, including on the best methods for normalization, weighting and aggregation. For example, while there may be widely agreed that health need, domestic capacity and expected impact are relevant concerns, there will be reasonable disagreement about their exact relative weights. At the same time, we found that the difference between the multi-criterion framework with equal weights and that with survey-informed weights was modest. More generally, while many methodological choices were somewhat arbitrary, we used simple and conventional methods throughout, with the aim of making the method as intuitive and transparent as possible. Future studies may examine the desirability and implications of different methodological choices in the specific context of DAH, including a comprehensive sensitivity analysis of these choices.Seventh, we examined implications mainly in terms of changes in rankings. This only provides an indication of the implications for most decisions on DAH. The final classification of countries depends not only on the dimensions in which countries are assessed but also on the thresholds applied within those dimensions. These thresholds may or may not link directly to decisions regarding eligibility and transition. Among the eligible countries, the levels of funding are likely to be guided not primarily by country rank, but by cardinal scores and absolute differences in the relevant indicators or indices. Future studies should thus go beyond the pure ranking of countries to examine cardinal scores, absolute differences and the implications of different thresholds.The complex landscape for DAH calls for carefully crafted allocation policies that go beyond GNIpc. The findings of this study can inform donors in assessing and reforming their policies. Specifically, donors have reasons to include one health-needs indicator in the initial classification of countries, and both life expectancy and DALYR are indicators worth considering. For most donors, the findings further suggest that indicators related to other concerns may be mainly relevant at different stages of the decision-making process, require better data or both.HEAPOL online.For the discrete choice experiment, an IRB human subjects exemption status was obtained from New York University.Supplementary File 1Click here for additional data file.Supplementary File 2Click here for additional data file.Supplementary File 3Click here for additional data file.


Better knowledge of the epidemiological characteristics of snakebites could help to take measures to improve their management. The incidence and mortality of snakebites in the Americas are most often estimated from medical and scientific literature, which generally lack precision and representativeness.Authors used the notifications of snakebites treated in health centers collected by the Ministries of Health of the American countries to estimate their incidence and mortality. Data were obtained from official reports available on-line at government sites, including those of the Ministry of Health in each country and was sustained by recent literature obtained from PubMed. The average annual incidence is about 57,500 snake bites  and mortality is close to 370 deaths , that is, between one third and half of the previous estimates. The incidence of snakebites is influenced by the abundance of snakes, which is related to (i) climate and altitude, (ii) specific preferences of the snake for environments suitable for their development, and (iii) human population density. Recent literature allowed to notice that the severity of the bites depends mainly on (i) the snake responsible for the bite (species and size) and (ii) accessibility of health care, including availability of antivenoms.The main limitation of this study could be the reliability and accuracy of the notifications by national health services. However, the data seemed consistent considering the similarity of the incidences on each side of national boundaries while the sources are distinct. However, snakebite incidence could be underestimated due to the use of traditional medicine by the patients who escaped the reporting of cases. However, gathered data corresponded to the actual use of the health facilities, and therefore to the actual demand for antivenoms, which should make it possible to improve their management. A better knowledge of snakebites incidence and mortality might improve their management. However, they are difficult to estimate, in particular because most of them are based on extrapolations from scientific and medical publications that are not representative of the epidemiological situation. This study, based on data available on-line at government sites in the Americas—reflecting notifications from health services—sustained by recent publications to provide useful information on snakebites treated in health centers of American countries. On average, nearly 60,000 snake bites are managed every year in health facilities in the Americas and approximately 370 deaths are reported officially. The development of snake populations results from environmental conditions favorable to their feeding and camouflage. Moreover, the activities of human—notably agricultural—explain encounters with the snakes. The literature underlines that the severity of the envenomation depend on the species responsible for the bite and quality of the management of the patient. Without excluding an underestimation of snakebite incidence, due to the frequent use of traditional medicine, this study should enable health authorities to better analyze the epidemiological situation of snakebites, including their frequency, distribution and severity, in order to improve the management of the envenomation. From a total of 4,514 references, 187 concerned the epidemiology and/or management of snakebites in the Americas.Furthermore, websites regarding i) the epidemiology of snakebites , ii) population demography (using the words “population demography”) and iii) administrative and environmental geography (using the word “map”) were identified using the Google search engine for each of the countries of America and using the official language of each country . Access to these websites was made between September 2010 and December 2016. The list of the websites and the last access date to each are mentioned in 2, the coefficient of determination that is the square of the coefficient of correlation indicates the extent to which the dependent variable is predictable, were calculated through Excel. The comparisons were made using parametric tests  or non-parametric (Mann-Whitney), depending on the distribution of studied variables and number of cases/groups. The significance level was equal to 0.05 and the means were expressed using a 95% IC. Statistical analyzes were performed using the BiostatTGV online software (http://marne.u707.jussieu.fr/biostatgv/).All the data were transferred and analyzed using Excel software. The trend curves and Rhttps://commons.wikimedia.org/wiki/Atlas_of_the_world) and drawn on the basis of the data obtained in this study.Topographic, physical and political maps were taken from the World Atlas of Wikimedia , resulting in almost 370 deaths , with a case fatality rate below 0.6% . HoweverThe data are detailed for each country according to the websites mentioned in Information is available online since 2007.2) and Misiones in the north-east with a higher density (35 inhabitants per km2) but predominantly agricultural. The seasonal distribution of envenomation showed a summer incidence five to six times higher than the winter one  and 5 deaths per year  during the 2007–2014 period. There was a steady decrease in annual incidence . The incnter one .Bothrops were responsible for 96.6% of the bites, Crotalus 2.8% and Micrurus 0.6%. Population at risk consisted of young men bitten during agricultural activities. Most envenomations (90%) were treated within the first four hours by an antivenom.These results corroborated those by Dolab et al.  obtainedNo information on snakebites has been obtained for Belize.However, on the basis of existing data from neighboring countries showing similar environments, the annual number of bites can be estimated at 35  and deaths at 1 every 2 to 4 years .The information is available online from 1996 but the notification was interrupted between 2001 and 2009. It returned to availability from 2010. The presentation of the data has been standardized, in particular as regards the classification of age groups. By 2015, the information has been supplemented by the addition of the gender of the patients. However, mortality from envenomation is still not provided.In their study on snakebites in Bolivia, Chippaux and Postigo  reported−4) between incidence and altitude.The annual incidence increased significantly between 2010 and 2015 . The disThe notification of snakebites is performed for a long time in Brazil but the results are online only since 2001. According to Chippaux , the aveBothrops species were responsible for most of the bites everywhere in Brazil. Bites by Crotalus durissus are more frequent in the eastern and central savannas. The bites by Lachesis sp. are mostly observed in the Amazonian region. Those by Micrurus sp. are rare. Finally, there was a strong inverse correlation between incidence and population density  with 2,000 deaths  in the study by Kasturiratne et al. .Nevertheless, the general incidence is much lower than in Asia or Africa ; 2; 61, Most of the data collected in this study comes from the Ministries of Health of the concerned countries.Until now, epidemiological surveys were needed to obtain information that was most often limited geographically according to the constraints and choices of the investigators. Sometimes methodological biases, particularly in site selection, led to approximations or significant errors in the estimation of the incidence or severity of envenomations . For theMandatory reporting of cases allows covering a country as a whole rather than a few sites chosen by the investigators, leading to poorly representative figures. However, data gaps and limitations are still observed resulting from a poor surveillance system. On the one hand, it is expected that over time the data collection will improve and on the other hand the standardization of the questionnaires will make it possible to have more robust, reliable and complete information. For example, useful, often missing data, particularly severity, treatment (brand and dose of antivenom) and clinical outcomes  need to be collected, which is not currently the case in most situations. However, in some countries , these data are available, showing that such a goal is feasible.It is rarely stated whether the notification of snakebites included asymptomatic bites, which is probably the case in most countries. Asymptomatic snakebites may result either from a bite by a non-venomous snake or a venomous one that did not inject venom (dry bite). According to the countries and authors, asymptomatic snakebites represent between 10 and 40%, about one third of which are dry bites ; 63; 64.As a consequence, the comparison with the recent literature has been very useful for, a) confirming (or supplementing) the data from other sources and, b) providing additional information, in particular on the clinical severity of envenomations, details on circumstances of the bite or implementation of the treatment.It was emphasized that the notification was not very precise and reliable, at least variable from one country to another. However, the reporting system improves over the time and, of course, provides a minimal—conservative—incidence of snakebites seen by healthcare institutions from which it can be inferred treatment needs, especially antivenoms. The increase in incidence observed in some countries  can be attributed to an improvement in data collection, particularly in the early years of its implementation. The stabilization or reversal of the upward trend confirms this. However, environmental (e.g. reduction of snake population) or demographic (population migration to urban centers with low snakebite risk (see below)) causes should not be underestimated. It is notable, for example, that the incidence is often similar on both sides of a border between two neighbor countries—despite likely differences in data collection efficiency -, reflecting a constant figure regarding both risk and population reaction to the snakebite. Actually, administrative policies are different on each side of the border, but populations are often the same on the both sides… It is known, for example, that many patients prefer to use alternative medicine rather than a modern treatment provided by health center. This occurrence is poorly addressed in Latin America, but it probably plays a significant role in underestimating the incidence and possibly severity  of envenomations. However, some inconsistencies can be explained either by different environmental conditions affecting the risk factors mentioned below, or by significant differences in the quality of the notifications. The report still suffers from inadequacies, resulting in underestimations of snakebite incidence and mortality in some regions of Latin America .The geographical distribution of the incidence was heterogeneous: it was higher in the intertropical region and in developing countries. The incidence depends mainly on environmental and anthropic factors that are detailed below.The number of deaths appeared to be more difficult to determine due to the lack of notification in several countries. However, these countries are generally sparsely populated regions, which limit the impact on the total result. We proposed here a reasonable estimate for each of these countries at the risk of a trivial error.2 indicates the proportion of the variance in the dependent variable that is predictable from the independent variable, i.e. it gives some information about the goodness of fit of a model. The closer R2 is to 1, the better the data match the model, but this does not mean the model is relevant.Basically, the incidence results from the encounter between a man and a snake. It is therefore legitimate to consider the activities and the presence of the first as well as the behaviors of the latter. It is difficult to explain what affects snakebite incidence because of the complexity of possible causes and their interactions, such as the biology of animal populations composed of many species or the demographics of human populations that are dependent on many social, economic, environmental factors. The coefficient of determination RIncidence tends to grow mechanically as a function of demography although there is a partial offset related to a decrease due to anthropization of the environment which reduces snake populations and/or snake-man contacts. In addition, the proximity of human populations to the natural environment explains a greater frequency of encounters with snakes. As a consequence, snakebites occur usually in rural areas during agricultural activities, especially in developing countries where farming is an important and weakly mechanized economic activity.Population density was sometimes inversely correlated with the incidence of bites, as in Brazil , suggestIsolated areas are the most affected, mainly due to lack of good roads linking urban centers and activities of the population performed in precarious conditions . These occurrences increase both the likelihood of encounters with snakes and the difficulty of receiving timely medical help. As a consequence, scarcity of health centers is a factor that indirectly influences the incidence of snakebites and directly (and significantly) affects the clinical outcomes of envenomations ; 44; 65.e.g. Bothriopsis taeniata, are absent or rare in anthropogenic areas, others come near to human settlements and may even grow there [Crotalus, e.g. C. viridis or C. oreganus in the USA [Bothrops, as Bothrops asper in Costa Rica [The abundance of snakes, especially species that inhabit cultivated or settled areas and sometimes even reproduce there, varies according to climatic (heat and humidity) and environmental (vegetation and landscape) factors that determine food supply, both qualitative and quantitative, and camouflage opportunities . While sow there , at leas the USA ; 69, or sta Rica , are attCrotalus simus and Bothrops asper), partially explaining the variation in the incidence of snakebites. Moreover, the DNCs of the two vipers, combined with the marginalization of human populations, accounted for 3/4 of the variation in incidence. Thus, several factors, environmental, socio-economic and sanitary, contribute to explain the incidence of snakebites.Ecological niche modeling (ENM) allows, using appropriate algorithms, to predict the geographic distribution of a species from climatic and environmental data. Yañez-Arenas et al.  used thePopulations at risk were very similar in most countries. While children and teenagers constituted an important part of the population, sometimes the majority in developing countries, they were not the mostly bitten. Population at risk was predominantly composed of young men between the ages of 15 and 45, living in rural areas and bitten during agricultural activities. This may explain why bites occur most often during hot (summer) and wet (rainy season) periods, usually at harvest time.The severity of the envenomation, in particular mortality, is related to the species, but also the size, of the snake responsible for the bite, which determine the composition of the venom and the quantity injected respectively ; 15; 71.a priori more vulnerable [Age of the patient appeared to be a risk factor, especially at both ends of life, in children and elderly persons–lnerable . HoweverIn addition, the mortality and incidence of complications–most notably the sequelae–depend on the management of snakebites, i.e. the health care system as a whole . For example, the significant decline in mortality in many countries–particularly in Costa Rica –32, EcuaHowever, other factors may also affect the mortality and severity of envenomations, such as the availability of health centers and treatment, which may be very irregular, particularly in remote areas where activities of the indigenous population are often very close to nature. The delay in treatment may thus compromise the clinical course of envenomation. Nevertheless, the treatment seeking behavior is complex and many patients, particularly in remote areas, still use traditional medicine. The latter should be associated with modern medicine in order to define relevant recommendations that do not put them into competition but optimize the therapeutic approaches to avoid complications and disabling sequelae as is still often the case.This study summarized the burden and epidemiological characteristics of snakebites in the American continent. The incidence and severity of envenomation appeared to be lower than previously assessed, although many risk factors have been already known and studied. This work showed the importance of mandatory reporting of snakebites to improve their management, provided that health authorities endorse, analyze and exploit the data.It therefore seems necessary to continue this effort, improve the case reporting system and take the measures that can be inferred from the obtained analysis of the available information.


An increased prevalence of the inflammatory bowel diseases, ulcerative colitis and Crohn’s disease, was found amongst residents in a livestock dense area. We hypothesised that exposure to livestock farms might be a substantial environmental factor that contributes to the development of these diseases and that in the lead up to inflammatory bowel diseases potential risk factors can be identified. This study aimed to investigate the contribution of livestock exposure to the development of these diseases and the clinical events prior to the diagnosis. Electronic health records from 2006–2013 of general practices were used. The study population consisted of patients with a new diagnosis of inflammatory bowel diseases resident in areas with a high (n = 141) or lower (n = 109) livestock density. Patients with low back pain  were used as controls. For those in a livestock dense area, distance to livestock farms was determined. Associations between morbidities and drug prescriptions in the reporting year and three years previous to the diagnosis, and the residential proximity to livestock exposure were investigated with multivariable logistic regression analyses. Acute and chronic morbidity of the gastrointestinal tract and associated drug prescriptions were predictive for the development of inflammatory bowel diseases. In addition, a positive association was found between infections and living within 500 meter of poultry farms and the development of inflammatory bowel diseases [OR: 3.3 (1.1–9.9)]. Nonetheless, overall livestock exposure contributed little to the development of these diseases. These results suggest that exposure to livestock farms on its own contributes minimal to the development of inflammatory bowel diseases. Nonetheless, having infections appeared to be a risk factor for neighbouring residents of poultry farms. More research is warranted to explain the increased prevalence of inflammatory bowel diseases amongst residents in areas with a high density of livestock. Ulcerative colitis and Crohn’s disease are chronic inflammatory diseases of the gastrointestinal tract (GI-tract) and are known as inflammatory bowel diseases (IBD). Ulcerative colitis is characterised by inflammation of the mucosal layer of the colon and rectum. In contrast, Crohn’s disease is characterised by transmural inflammation causing strictures and fistulas, and may affect the entire GI-tract. Clinically, ulcerative colitis often manifests with abdominal pain and diarrhoea associated with blood, while Crohn’s disease often manifests with abdominal pain and constipation. However, in practice the distinction between these two diseases can be a challenge, resulting in diagnostic delays for months in adults up to several years in children ,2. AlthoAs the diagnostic process of IBD can be challenging, longitudinal studies investigating the clinical events preceding this diagnosis are warranted. In one such study, Pimentel and colleagues showed that the clinical threshold of IBD-related symptoms were present on average seven years before diagnosis . WhetherThis study was designed to investigate whether livestock exposure contributes to the development of IBD and whether potential risk factors can be identified. To this end, we investigated clinical events preceding the diagnosis of IBD using health records in the reporting year and three previous years to the diagnosis of these diseases. These records were gathered for residents in a rural area with a high density of livestock farms and residents in rural areas with a much lower density of those farms, and findings compared to those gathered in a control group.A case-control study was performed using electronic health records (EHRs) of general practitioners (GPs) in the Netherlands. These records include morbidity and drug prescriptions at the patient level. Clinical events in the reporting year and three previous years to the diagnosis were investigated for patients with IBD, the cases, in comparison with patients with low back pain with or without radiating pain, the controls. Patients with low back pain were included as controls since these patients constitute typical general practice patients who also contact and visit the GP regularly, but their symptom patterns and associated healthcare utilisation are theoretically unrelated to IBD, as well as livestock exposure . In addiResearch was performed in accordance with the Dutch Medical Treatment Act and Personal Data Protection Act. The protocol of the VGO study was approved by the Medical Ethical Committee of the University Medical Centre Utrecht. Privacy was ensured by using a Trusted Third Party , keeping medical information and address records separated at all times.r.coppen@nivel.nl) or non-personal departmental email , or contact Christos Baliatsas, PhD , Lidwien Smit, PhD (l.a.smit@uu.nl) or Joris Yzermans, PhD (j.ijzermans@nivel.nl).In consultation with the Medical Ethical Committee that approved the study protocol, data from the VGO study are not publicly available due to privacy protection of participants. The study's privacy regulations stated that only co-authors and researchers from NIVEL, IRAS, and RIVM (consortium partners) have access to the study database and researchers who are not part of the consortium partners will not have access to the study database since sharing an anonymized and de-identified dataset would still contain Electronic Health Records and the personal data of participants, which could potentially lead to the identification of subjects. Researchers may reach a data transfer and privacy agreement to access the data, which will include agreement on co-authorship with the consortium members who were responsible for designing the study and collecting the data. Researchers may contact the data access committee through Remco Coppen, PhD, LLM  between 1 January 2006 and 31 December 2013 were used. The practices are representative of the Dutch GP population with respect to age, gender, region and urbanisation . FurtherFollowing the selection of practices, incident patients with IBD and low back pain were identified according to their first registration of IBD or low back pain in their EHR. GPs registered the reason of contact, including diseases and presented symptoms, according to the International Classification of Primary Care (ICPC) . In thisHealth records in the reporting year and three previous years to the diagnosis were investigated for all patients using the ICPC-classification for morbidity and the Anatomical Therapeutical Chemical (ATC)-classification for drug prescriptions. In the ATC-classification, drug prescriptions are classified “according to the organ or system on which they act, and their therapeutic, pharmacological and chemical properties” . In ordeDetailed information on livestock farms was used to investigate the influence of livestock exposure to the development of IBD. The provinces of Noord-Brabant and Limburg provide mandatory licenses and therefore retain information among others on the number of livestock farms and type of animals, including pigs, poultry and cattle. As previously described, the distance between the patients’ residences in the exposed area and livestock farms was calculated by a geographic information system using the residential addresses and area codes  ,17,20. Ct test.Differences in total healthcare utilisation for cases and controls between the exposed and reference area, including mean number of presented morbidity and drug prescriptions from all years together, was tested using the Mann-Whitney U test. Differences in gender and age at diagnosis between those areas as well as between cases and controls were tested using the Student’s In order to investigate potential associations between incidence of IBD and morbidity and drug prescriptions in the reporting year and three previous years to the diagnosis and to investigate whether the area of residence modifies these associations, logistic regression analyses were performed. Inflammatory bowel disease—‘1’ was IBD, ‘0’ was low back pain—was used as the dependent variable and the presence of the morbidity and drug prescription clusters were used as independent variables. Separate analyses were performed for each independent variable, and results were corrected for gender and age at diagnosis. Results were stratified for the area, and p-values for the multiplicative interactions  are shown.To investigate the influence of livestock exposure as an environmental factor to the development of IBD, logistic regression analysis was performed. Development of IBD was the dependent variable and livestock exposure the independent variable. Again, correction was performed for the potential confounders gender and age at diagnosis. Expanding on this analysis, the influence of livestock exposure variables, such as type of livestock, as effect modifiers was investigated in the exposed area. Results were stratified for the exposure variable, and p-values for multiplicative interactions  were determined from combined models.Finally, given the hierarchical structure of the data, analyses were repeated on the basis of multilevel logistic regression to verify consistency of the results. Multilevel analyses showed similar results and are therefore not presented. Stata  was used to perform all analyses.Details of the study population are shown in p for interaction = 0.25). In contrast, residents with infections of the GI-tract in the reference area were more at risk for development of IBD than those in the exposed area .In general, drug prescriptions were positively associated with the development of IBD . In partWithin the exposed area, an indication was found for an inverse association between the presence of livestock farms within 500m of the patients’ residences and the development of IBD. However, it did not reach conventional levels of statistical significance . The association with the number of livestock farms within 500m was in the same direction, with an odds ratio of 0.98 (95%CI: 0.9–1.1) per farm compared with residents who did not live within 500m of livestock farms in this area.p = 0.006 for interaction, Positive and statistically significant associations between infections in the reporting year and three previous years to the diagnosis and the development of IBD were only found among those living within 500m of poultry farms, in particular for infections of the airways  and categories  of morbidity according to the ICPC-classification of symptoms and diseases .(DOCX)Click here for additional data file.S2 AppendixDrug prescriptions and clusters of drug prescriptions according to the guidelines for ATC classification and Defined Daily Dose assignment 2015 .(DOCX)Click here for additional data file.