>> Larissa Aviles-Santa: Now, I will highlight
a few reviews that shed light on opportunities to do research
or to fill gaps in research
related to disasters and humanitarian crises.
In this scoping review of health and research
linked to disasters in 43 low- and middle-income countries,
the investigators identified earthquakes and tsunamis
as the most common disasters in the selected articles.
About half of the articles, in terms of the methods,
they consisted of cross-sectional studies,
and 17 percent of them, retrospective analysis.
And they also reported mixed methods
used in hurricane-related and tsunami-related studies,
but it was in less than half of them.
In terms of research topics,
mental health was the most common research topic,
and, of note, mental health
tends to be one of the first interventions
in disaster relief and recovery,
and a common research topic in disaster research.
Now, congruent with the common disasters
that were reported in the articles
that were chosen for the review, traumatology and surgery
would be expected to be among the top research topics,
so that's congruent with the findings.
In contrast, chronic conditions,
non-communicable and chronic diseases here,
made less than 2 percent of the literature in low-
and middle-income countries.
Chronic, non-communicable diseases
have been increasingly recognized in low-
and middle-income countries,
to which a great public health burden has been attributed.
More attention to this area of research,
especially in the management of chronic diseases,
should be emphasized.
In this other scoping review on natural disasters
in the Caribbean,
the authors included 17 articles published
between 1974 and 2020.
They noted that most of the articles
were descriptive and qualitative,
and they also noted that the burden and management
of chronic diseases was often overlooked.
But they also observed some challenges
and potential strategies within the context
of the management of chronic diseases.
And the challenges were basically categorized
into two groups,
disruptive healthcare systems and food insecurity.
And within disruptive healthcare systems,
that manifested at least in a limited access
to medications, remote medical advice,
or direct in-person visits; infrastructure problems,
especially on the disruption of supply and cold chains;
structural damages of the healthcare facilities;
and disruption of communications.
In terms of strategies,
to enhance access to medications,
some investigators recommended
and or tried a centralized pharmacy registry,
medication distribution centers,
incorporating pharmacists into the dispensation of medications,
especially at evacuation shelters,
and trying alternative medications
when the brand name medications were not available.
Importantly, education of the individual, of the patient,
on being prepared for any catastrophe for power outages,
for prolonged and problematic access to medications,
and on self-management,
was important and highly recommended.
And capitalized on social media when the internet is available,
because social media can reach out multiple
people and promote education to a large group of individuals.
And they definitely pointed out that robust surveillance systems
are key for the identification of non-communicable diseases,
but also tracking its management.
In this publication,
the authors discussed the potential consequences
of disasters in different healthcare system scenarios.
And they are using modelling to demonstrate
the potential effects.
The authors define surge capacity as,
"the provision of medical care
to a large volume of persons during an active response",
and secondary surge capacity as,
"the sustained ability of the healthcare system
to expand operational resources to meet the increased need
and demand during the long-term recovery."
So, using this model, in this first diagram
that you are seeing on the screen,
the authors illustrate a scenario
in which the primary care needs are met
and the system is working under capacity.
You can see that the system, the primary care needs,
are below the maximum surge capacity.
Within this context or example, the system is able to absorb
or to respond to the acute response
and to manage the healthcare needs
without being overwhelmed or going overboard.
So, the system remains stable throughout the response
and the recovery.
In this second example,
the system is under capacity at baseline,
like the previous system.
The disaster, or the event, occurs,
but the primary care needs eventually start to increase,
and this may happen when factors outside of the healthcare
are affected, for instance we have mentioned power outages,
or maybe roadblocks,
or problems with transportation, or food insecurity.
I'm going to promote exacerbation of chronic diseases
and therefore a higher demand of medical services
sometime after the event and the response.
So, the system becomes suddenly over capacity,
but the system has the ability to respond
and come back to normal. So, in this case,
the system can manage and recovers a few years later.
In the third scenario, the system is also at less
than capacity or less than maximum at baseline,
the disaster or the event happens,
but the overwhelming number of complications
now exceeds much more than what the system can handle
and the recovery or the return to normal is unknown.
And this may be to due to characteristics
of the population in addition to other factors
outside of healthcare, for example,
do we have people with multiple chronic diseases
in this community?
And do we have people with disabilities
and who need certain services
like dialysis or children with special needs?
And so, depending on the characteristics
of the population and other factors, they merge,
and the ability of the system to respond
in the long-term is affected.
In the fourth scenario, it's a system in which the population
has baseline health or healthcare disparities.
So, at baseline, that system is already overwhelmed.
The system is not able to really provide all the services
and supply all the needs that the population has.
This is our baseline.
When the disaster happens, or the event happens,
then the system,
which is already overwhelmed, overboard,
is going to be even more overwhelmed
and definitely a return to baseline is unknown,
much more than Scenario C.
I would like to point out a couple of things
about this modelling,
which is very helpful to understand the possibilities
when we are working in disasters,
and especially within the context of populations
with health disparities or healthcare disparities.
First, in these diagrams, the events are similar.
They are similarly shaped, a similar lens.
I mentioned before that disasters vary
by type and intensity and magnitude,
so if a disaster is of lesser magnitude, or greater magnitude,
the shape of the curves and the ability to come back
to normal may vary depending on the scenario.
Other factors that could influence the shape
of this curve and the potential responding
is going to be migration or medical personnel,
because in the same way that the general population,
the community, may migrate because of the circumstances
are not really appropriate to remain
in the place where they used to live,
the same thing can happen to the healthcare workforce.
They can also migrate.
Also, the physical damages to health facilities,
the disruption of transportation and delivery of medications,
and other factors that we have already mentioned,
may prolong the recovery.
And the systems the return to normal,
and especially in this scenario D,
we don't even know, will they come back to baseline?
This baseline, which is already overwhelmed,
will they become to a much lower baseline?
Will they become stronger, more efficient?
Or will they have a higher baseline?
What will be the impact of the disaster?
And my other comment is, we know,
and I mentioned at the beginning,
some of us live in areas that are prone to not one,
not two, but multiple disasters. So, how would this model look
within the context of communities
that are exposed to disasters in a cyclical manner?
Those are questions that are important to ask and answer
because that will give us a better idea
on how to prepare that population,
how to prepare those healthcare systems.
This is a related example
to the modeling that I just mentioned,
but this is real life. And this is not a review,
this is information from two hurricanes,
and it's based on tracking on the opening of pharmacies
in Puerto Rico after Hurricane Maria
that happened in 2017,
and the opening of pharmacies in Florida after Hurricane Irma
that happened more or less in the same month,
September of 2017.
But again, Florida is a state, it's mainland United States,
and Puerto Rico is a U.S. territory,
it's an archipelago in the Caribbean.
In this figure we see
that pharmacies operating rate in Florida
in the blue-gray dots that you see,
90 percent of the pharmacies were already opened by day four.
It took about four days for the pharmacies
to be completely open, or back to normal.
But it took 31 days in Puerto Rico
to start seeing some kind of normalcy,
and also, overall, pharmacy operations in Puerto Rico
recovered 10 times slower
compared to pharmacy operations in Florida.
And this during the same hurricane season.
What is the difference?
I mentioned a couple of differences.
Puerto Rico is an archipelago in the Caribbean,
Florida is mainland U.S. If hurricanes hit Puerto Rico,
85 percent of the goods in Puerto Rico are imported,
so when the hurricane hits, transportation, the weather,
doesn't allow for the normal transportation
and business to take place.
Also, there was a massive power outage across the archipelago,
so internet communication and even telephone communication,
all digital communication, was impaired for a long time.
So, these circumstances,
these are examples of non-healthcare factors
that impact health and health services during disasters.
So, considering the challenges, strategies,
and the published health research
linked to humanitarian crises,
and the gaps in research that we have discussed,
it is clear that some of these gaps
could be turned into opportunities.
And the following is a non-exhaustive list of topics
or research questions.
We talked about research methods and ethics,
and demographic changes and subsequent healthcare needs,
especially on the projected impact on healthcare systems.
The long-term effects on health and healthcare systems,
especially anticipated needs
in an overwhelmed or fragile system.
How medical referrals and specialized
health services during disasters,
and the impact of healthcare workers migration
and relocation.
The burden and management of chronic diseases
and how to maintain continuity of care during these events,
and reducing the disruption
to access to medications and devices
and preventing hospitalizations and fatalities.
Also, effective ways to really implement
emergency preparedness and recovery plans;
strategies to maintain operations;
coalitions of hospitals, clinics,
non-profit organizations, community organizations,
schools, academic institutions, non-academic institutions;
transport service with specific carry units;
planning for people who have specific healthcare needs
that could go to a place where those could be provided;
providing fuel, water, food, medication storage.
Effects of pre-existing policies,
like we mentioned before, community
and healthcare partnerships,
important that, in some communities,
local leaders are very creative
and they are working at home, with the community,
on preventing problems and also maintaining health,
and how those ideas and strategies
could be through a performed
or in a collaboration with healthcare systems.
Training of workforce and the impact of serial
or multiple disasters.
And something I mentioned at the beginning,
despite all the circumstances,
despite all these multiple adversities,
some individuals and communities maintain a degree of resilience
that could shed a lot of light to us, to anyone.
Resilience that could be from molecular level
to population level,
and what we can learn that we could implement
and prepare for disasters better.