Strict lockdown policies in Peru have done little to curb the spread of Covid-19

GlobalData Healthcare 19 June 2020 (Last Updated June 19th, 2020 15:06)

Strict lockdown policies in Peru have done little to curb the spread of Covid-19

There are now more than 237,000 confirmed cases of the coronavirus disease 2019 (Covid-19) and more than 7,000 deaths due to Covid-19 in Peru. The number of cases reported in Peru is the second highest in Latin America. Since early April, the death rates of Covid-19 in Peru have surpassed the death rates reported in Mainland China. Strict lockdown measures in Peru have done little to curb the spread of Covid-19. Testing capabilities and contact tracing will be crucial to isolate the virus and limit transmission now that Peru has started a gradual reopening of the economy.

Peru is ranked as the eighth most heavily affected country globally. Although Peru was one of the first Latin American countries to implement a strict nationwide lockdown, it has become one of the major hotspots for the Covid-19 outbreak in the region. Several factors lead to the rapid increase in cases despite early measures to curb the spread of the virus, among them being people unable to follow the lockdown rules due to social and economic inequalities.

On 16 March, Peru implemented strict lockdown measures to keep its population at home and limit the number of people congregating in the same areas and spreading the virus. However, since then, lockdown cases in Peru have only continued to increase at an alarming rate. Currently, Peru has not been able to flatten the curve. The country reported more than 50% of its total confirmed cases of Covid-19 in just the three weeks leading up to June 14. Some of the reasons why lockdown has not yielded the expected results are that a large proportion of the Peruvian population has not stayed home. Some residents, for example, need to venture out frequently for necessities as their homes lack access to running water and food storage options. According to the Peruvian National Institute for Statistics (INEI), approximately 51% of the homes in Peru do not have a refrigerator. This makes it difficult for people to store food for more than a few days and leads them to go out several times a week to buy food in already crowded markets. Additionally, poor households, which are already more vulnerable to coronavirus infection, are less likely to have access to running water indoors and by extension are less likely to follow the primary prevention measure of frequent handwashing. Another barrier preventing people from staying home was the large proportion of Peruvian adults without some type of financial product such as a checking or saving account (approximately 56% according to INEI), causing people to form long lines outside of banks in order to collect government aid.

GlobalData’s forecast for Peru shows that the country may have reached its peak in the first week of June (Figure 1). The average daily new cases in the week of June 7–14 are approximately 900 cases lower than the week before. For the week of May 31–June 6, the average daily new cases were approximately 1,500 cases higher than the week before (Figure 1). Lockdown in Peru was recently extended to the end of June but will be less strict to allow the continued reopening of businesses such as hair salons, dental services, and household appliance stores. Peru will need to remain vigilant and continue to develop its testing capabilities, especially among workers and visitors in areas of high contagion like food markets and banks to ensure a consistent decline in new daily cases. Contact-tracing, as the economy reopens distancing, is crucial to stop the chain of transmission by isolation the virus and preventing a new surge. Based on current data, GlobalData does not expect Peru to enter recovery until the end of August; however, continued monitoring of new cases and country trends are needed to determine its future trajectory (Figure 1).

Figure 1: Peru, Modeled Forecast of Covid-19 Trajectory of New Cases.

Source: GlobalData; Alva, 2019; INEI, 2018