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@@ -231,7 +231,7 @@ <h1 class="title">Climate And Statistics</h1>
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 <h1>Preface<a href="index.html#preface" class="anchor-section" aria-label="Anchor link to header"></a></h1>
 <p><em>Author: Henri Funk</em></p>
-<p><img src="cover.jpg" width="500" style="display: block; margin: auto;" /></p>
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 <p>As the world faces the reality of climate change, natural hazards and extreme weather events have become a major concern, with devastating consequences for nature and humans. The quantification and definition of climate change, extreme events and its implications for life and health on our planet is one of the major concerns in climate science.</p>
 <p>This book explains current statistical methods in climate science and their application.
 The methods include compound events, low flow events and return periods, natural variability, teleconnections and causal discovery.

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@@ -237,9 +237,6 @@ <h2><span class="header-section-number">7.1</span> Concept of Extremeness by Ret
 <span class="citation">(<a href="#ref-du"><strong>du?</strong></a>)</span></li>
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-<p><em>Author: Lennart Marx</em></p>
-<p><em>Supervisor: Henri Funk</em></p>
-<p><em>Degree: Master</em></p>
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@@ -240,7 +240,7 @@ <h2><span class="header-section-number">13.2</span> 2. Challenges of Quantifying
 Although in the IPCC report most of the adverse effects of CC on MH are assessed with “very high confidence”, no concrete projections are given as to how many additional people will suffer from mental disorders. This is peculiar because for other health effects that are assessed with very high confidence, figures for additionally affected individuals are given <span class="citation">(<a href="#ref-intergovernmentalpanelonclimatechangeClimateChange20222023">Intergovernmental Panel On Climate Change 2023</a>)</span>.
 The discrepancy between confidence and tangible figures is caused by multiple challenges of attributing CC to MH, which can be clustered in external and internal difficulties. The external difficulties of quantification mainly consist of the globally insufficient resources devoted to monitoring and treating MH. Although the Lancet Countdown emphasised the need to integrate MH in future CC health considerations, only five out of 16 countries included MH in their health adaption plans <span class="citation">(<a href="#ref-watts2018ReportLancet2018">Watts, Amann, Arnell, et al. 2018</a>)</span>. In the most recent Countdown report it was noted that the development of an indicator to cover the relations between CC and MH is still ongoing <span class="citation">(<a href="#ref-romanello2023ReportLancet2023a">Romanello, Napoli, et al. 2023</a>)</span>. One major problems hereby is that current prevalence estimates for mental illnesses are unreliable, as mental illness is severely underdiagnosed, especially in third world countries <span class="citation">(<a href="#ref-worldhealthorganizationComprehensiveMentalHealth2021">World Health Organization 2021</a>)</span>. With the lack of a baseline, good projection estimates are difficult.
 The internal difficulties of quantification evolve around the complex nature of MH itself. Hayes et al. (2018) identified four key aspects which complicate the estimation of CC impact: Firstly, the risk of pathologizing normal stress responses due to a changing climate while adverse mental health outcomes are underdiagnosed. Secondly, multiple causal pathways in which one CC correlate can influence different MH outcomes. Thirdly, effects of CC may only become apparent after a considerable time period, which complicates the investigation of causal effects. Lastly, existing complex interactions between MH and other social determinants of health, and their relationship with CC, is insufficiently understood.</p>
-<p><img src="work/12-mentalhealth/figures/drought_impact.png" width="550px" style="display: block; margin: auto;" /></p>
+<p><img src="work/12-mentalhealth/figures/drought_impact.png" width="80%" style="display: block; margin: auto;" /></p>
 <p><em>Figure 1.</em> <font size="2">Causal process diagram of the impact of drought on the mental health outcomes depression, anxiety and suicide. Numbers in brackets are number of papers meeting the search criteria for each factor. Figure adapted from Vins et al. (2015).</font></p>
 <p>The four aspects can be illustrated by a causal process diagram, shown in Figure 1, which depicts the multiple pathways by which droughts can influence MH outcomes <span class="citation">(<a href="#ref-vinsMentalHealthOutcomes2015">Vins et al. 2015</a>)</span>. Most apparent is the economic route: Droughts have a negative impact on crop yield, influencing employment and financial stability in the agricultural sector. Financial hardship has been shown to have a negative impact on MH, leading to depression and, in severe cases, even suicide <span class="citation">Edwards, Gray, and Hunter (<a href="#ref-edwardsImpactDroughtMental2015">2015</a>)</span>. Another causal route is the one concerned with the decreased availability of food, leading to dietary changes or famine. This can directly influence neurodevelopment of children or anxiety in adults, but also indirectly cause migration, which can lead to social isolation and loss of cultural identity, again having a negative impact on MH outcomes. To estimate the impact of droughts on MH e. g. via the migration route, it would require not only to estimate the increase and severity of droughts due to CC, but also how much migration this would cause and how many of the affected individuals would consequently develop a mental illness. This is a genuine challenge for accurate climate projections, as estimation of migration movements and the development of mental illness depend on many interrelated factors <span class="citation">(<a href="#ref-mazhinMigrationHealthCrisis2020">Mazhin et al. 2020</a>)</span>. Some individual linkages between events (e. g. the influence of economic hardship on MH) are well-researched. Future research needs to integrate these pathways and link them to different climate scenarios to better understand the overall causal processes and make accurate projections possible <span class="citation">(<a href="#ref-vinsMentalHealthOutcomes2015">Vins et al. 2015</a>)</span>.</p>
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@@ -312,7 +312,7 @@ <h2><span class="header-section-number">13.4</span> 4. The Impact of Hurricanes
 <p><em>Note.</em> <font size="2">CI, confidence interval; OR, odds ratio; PTSD, posttraumatic stress disorder. Effects estimated with multiple logistic regression model controlling for sociodemographic variables, baseline value of PTSD and subsample. Reference category were participants with no hurricane-related stress. Significance level was 0.05.</font></p>
 <p>The study has four mayor limitations: First, in addition to the mentioned selection bias after the first screening, the dropout rate between measurement points was 21.9%. Although a weight was used to account for the selection bias, it is possible that other, non-collected variables might influence participation or dropout. Second, only screening scales instead of diagnostic interviews were used for diagnosis. Hurricane-related stress was measured using self-assessment questionnaires, which is both subjective and retrospective and possibly biased by current emotional functioning. Third, although interpreted causally, hurricane-related stress and PTSD might be influenced by unmeasured common causes, influencing the observed association. Lastly, there is no true pre-hurricane baseline for the sample, and preexisting mental illness was not recorded in the survey.
 The results of the presented study are partially contradicting similar studies which found a decline in PTSD over time <span class="citation">(<a href="#ref-chenIncidencePosttraumaticStress2015">Chen and Liu 2015</a>)</span>. The authors hypothesise that the increase in prevalence in the non-metro subsample may be caused by greater media attention and resources being allocated to the New Orleans metropolitan region, leading to a sense of neglect and slower reconstruction of infrastructure in other areas. It is also remarked that other stressors only indirectly linked to the hurricane, such as economic stress or displacement, might influence MH outcomes. This is an interesting point of discussion, as it shows that the IPCC categorization of climate change exposures impacting MH is not as simple as outlined before. Events that fall into the category of direct exposure, such as hurricanes, might have prolonged effects on mental health outcomes, e. g. via economic hardship. This in turn makes it very difficult to attribute MH outcomes to specific CC events, as effects can be observed directly after the event, but can also have a prolonged onset. The potential causal pathways of short-term and long-term stressors on PTSD are depicted in Figure 2.</p>
-<p><img src="work/12-mentalhealth/figures/DAG_hurricane.png" width="450px" style="display: block; margin: auto;" /></p>
+<p><img src="work/12-mentalhealth/figures/DAG_hurricane.png" width="75%" style="display: block; margin: auto;" /></p>
 <p><em>Figure 2.</em> <font size="2">Potential direct and indirect causal pathways through which hurricanes might influence the development of posttraumatic stress disorder (PTSD).</font></p>
 <p>To conclude, the study shows that disaster-related stress does play a significant role in PTSD outcome. Since adverse effects are only weakly related to socio-demographic variables, efforts for sufficient treatment must extend to the entire population. High residual hurricane-related stress after two years and its strong relation to PTSD emphasizes the need for evidence-based measures to address residual stress in multiple ways, ranging from rebuilding infrastructure to providing counselling and financial support.
 Although the study itself does not link the results to CC, it would be possible to draw a connection between this single, natural disaster and future CC impact on MH. According to the IPCC (2023), hurricanes are projected to increase in frequency and severity. If, as claimed in the study, hurricane-related stress plays a causal role in the development of PTSD, this increase in hurricanes would have a considerable effect on the number of individuals suffering from PTSD and would need to be taken into account for future health care adaption plans.</p>
@@ -321,7 +321,7 @@ <h2><span class="header-section-number">13.4</span> 4. The Impact of Hurricanes
 <h2><span class="header-section-number">13.5</span> 5. Adaption and Mitigation Strategies<a href="menh3.html#adaption-and-mitigation-strategies" class="anchor-section" aria-label="Anchor link to header"></a></h2>
 <p>Although the IPCC classifies the adverse impact of CC on MH to be of very high confidence, little attention has been directed to mitigation and adaption strategies for mental health and treatment systems <span class="citation">(<a href="#ref-charlsonClimateChangeMental2021">Charlson et al. 2021</a>)</span>. In Berry et al. (2018), a possible approach to deal with the high complexity of the matter is outlined. They criticise that today’s policies and epidemiological research is focused mainly on individual outcomes, proximate causes and measurements on short timescales. To address the impact of CC on MH more holistically, they propose “systems thinking”, which they define as a set of skills used to examine interacting factors that produce outcomes, predict their behaviour and design interventions. More precisely, in research they demand a mixture of CC projections and experimental designs to understand causal influences. In policy, behaviour change should be accomplished through social policy and collective actions instead of aiming at individuals. In direct actions and interventions, they demand a shift from the single-hazard perspective of e. g. extreme weather events to a strategic long-term planning accounting for an increase in those extreme events <span class="citation">(<a href="#ref-berryCaseSystemsThinking2018">Berry et al. 2018</a>)</span>.
 An example for system thinking would be the protection of infrastructure to benefit MH. This sounds far-fetched, but considering that the cost of damage to critical infrastructure is estimated to increase tenfold <span class="citation">(<a href="#ref-forzieriEscalatingImpactsClimate2018">Forzieri et al. 2018</a>)</span>, and that these costs divert resources from public health, put pressure on the functioning of society and take up individual resources – all factors that have a negative impact on MH – infrastructure protection could be a promotional strategy to protect MH from the impact of CC. The causal diagram of this process is depicted in Figure 3.</p>
-<p><img src="work/12-mentalhealth/figures/DAG_infra_2.png" width="450px" style="display: block; margin: auto;" /></p>
+<p><img src="work/12-mentalhealth/figures/DAG_infra_2.png" width="75%" style="display: block; margin: auto;" /></p>
 <p><em>Figure 3.</em> <font size="2">Top-level process diagramm depicting linkages between climate change, infratructure and mental health, as shown in Berry et al. (2018).</font></p>
 <p>The proposal by Berry et al. (2018) is a broad framework that may be useful to approach most of the problems discussed in this chapter. However, the individual components are yet to be tested in future research and policy designs.
 On the more practical side, Hayes et al. (2018) and Newnham et al. (2020) proposed several practical measures that could protect MH from direct and indirect CC impact. For acute response to disaster, first-aid responders and nurses need to be trained in basic psychological first aid. It has also proven beneficial for subsequent MH outcomes to prepare people living in vulnerable areas (e.g. near rivers that will flood more frequently in the future) for the possibility that the event might occur <span class="citation">(<a href="#ref-munroEffectEvacuationDisplacement2017">Munro et al. 2017</a>)</span>. Intermediate adaption could include capacity building for therapy and counselling, education and programmes to reduce stigma as well as community-building and preparation training for extreme weather-related events <span class="citation">(<a href="#ref-newnhamPreparingMentalHealth2020">Newnham, Titov, and McEvoy 2020</a>)</span>. Long-term prevention and mitigation require governments to include MH in their strategic health planning and the development of tools to predict risks, costs and needed resources. Ultimately, a swift transition towards a carbon-neutral economy would be the most cost-effective and efficient way of protecting MH from the impacts of CC.</p>